
Dieses Jupyter Notebook widmet sich der Vorhersage von Weinqualität des Vinho Verde.
Vinho Verde, oder auch der grüne Wein ist ein junger portugisischer Wein, der aus den Anbaugebieten zwischen den Flüssen Douro und Minho im Norden Portugals stammt.
Als Rebsorten dienen unter anderem Alvarinho, Avesso,
Loureiro und Trajadura. Gelegentlich wird auch die Rebsorte Sercial verwendet.
Das Leben ist zu kurz, um schlechten Wein zu trinken.
- Johann Wolfgang von Goethe.
Um die Trainingsprozesse zu verkürzen kann man einen Schnelldurchlauf aktivieren. Dieser wurde aus den Ergebnissen des Hyperparametertrainings erstellt und enthält bereits beschränkte Parameterbereiche, die zu einem ausreichend guten Ergebnis führen. Dies verkürzt die Laufzeit von Stunden auf <3 Minuten. Die kompletten Durchläufe befinden sich in den CSV-Datei in dem "results" Ordner.
Die Evaluation/Ergebnisse richten sich nach diesen CSV-Dateien.
# Professor oder Kommiltonen?
test_for_professor = False
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import itertools
import time
from scipy import stats
from sklearn.preprocessing import MinMaxScaler, StandardScaler
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import RepeatedKFold, KFold
from sklearn import metrics
from sklearn.pipeline import Pipeline
from sklearn.svm import SVR
import matplotlib.patches as mpatches
# Warnings wurden am Ende rausgefiltert, da "FutureWarnings" durch ältere Funktionen - welche für uns sinnvoller erschienen -
# erschienen und beim flüssigen Lesen stören.
import warnings
warnings.filterwarnings('ignore')
seed = 42
Definierte Hilfsfunktionen (hauptsächlich für Grafiken), um ein flüssigeres Lesen zu ermöglichen.
def plot_correct_prediction_pairplot(y, y_pred, df):
"""Pairplot, um die Lokalität der falschen Vorhersagen darzustellen
Args:
y (np.array): Labels des Datensatzes
y_pred (np.array): Vorhersagen des Modells
df (pandas.DataFrame): DatenFrame des Datensatzes
"""
plot_df = df.copy(deep=True)
plot_df["correct_prediction"] = np.equal(y, np.round(y_pred))
plt.rc('axes', labelsize=14)
plt.rc('xtick', labelsize=16)
plt.rc('ytick', labelsize=16)
p = sns.pairplot(plot_df.drop("quality", axis=1), hue="correct_prediction",palette = sns.color_palette("tab10", n_colors=2), plot_kws={'alpha': 0.5})
def plot_metrics_ensemble(y_test, y_pred, predictions, modelname="MODELNAME"):
"""Plot der Metriken Accuracy, Mean Absolut Error, Mean Squared Error
Args:
y_test (np.array): Labels des Testdatensatzes
y_pred (np.array): Vorhersagen des Modells
modelname (str): Modellname für die Plots, Defaults ist "MODELNAME"
"""
metric_list = np.asarray([[metrics.accuracy_score(np.round(predictions[0]),y_test), metrics.accuracy_score(np.round(predictions[1]),y_test), metrics.accuracy_score(np.round(y_pred),y_test)],
[metrics.mean_absolute_error(predictions[0],y_test), metrics.mean_absolute_error(predictions[1],y_test), metrics.mean_absolute_error(y_pred,y_test)],
[metrics.mean_squared_error(predictions[0],y_test), metrics.mean_squared_error(predictions[1],y_test), metrics.mean_squared_error(y_pred,y_test),]
])
plt.figure(figsize=(8,6))
ax = plt.subplot(1, 1, 1)
p = sns.heatmap(metric_list, annot=True, linewidths=.5, cbar = False, annot_kws={"fontsize":18})
p.set_yticklabels(["Accuracy", "Mean Absolute Error", "Mean Squared Error"], size = 16, rotation=0)
p.set_xticklabels(["SVR", "RFR", "Ensemble"], size = 16)
ax.set_title("Ergebnisse "+modelname+" (Testdatensatz)",fontsize=20)
plt.tight_layout()
plt.show()
def plotEverything_2(df):
"""Plot aller Features des DataFrames
Args:
df (pandas.DataFrame): DatenFrame
"""
plt.figure(figsize = (12, 20))
plotnumber = 1
for col in df:
if plotnumber <= 12:
ax = plt.subplot(6, 2, plotnumber)
p = sns.distplot(df[col])
plt.xlabel(col, fontsize = 14)
plt.ylabel('')
plotnumber += 1
plt.tight_layout()
plt.show()
def plot_correlatedfeatures():
"""Plot der Features mit den höchsten Korrelationen zueinander
"""
fig, axes = plt.subplots(1,3,figsize=(25,8))
p = sns.regplot(ax=axes[0], x="density", y="alcohol", data=df, line_kws={'color': 'grey'})
p.tick_params(labelsize=16)
p.set_xlabel(p.get_xlabel(),fontsize=22)
p.set_ylabel(p.get_ylabel(),fontsize=22)
p = sns.regplot(ax=axes[1],x="density", y="residual sugar",data=df, line_kws={'color': 'grey'})
p.tick_params(labelsize=16)
p.set_xlabel(p.get_xlabel(),fontsize=22)
p.set_ylabel(p.get_ylabel(),fontsize=22)
p = sns.regplot(ax=axes[2],x="chlorides", y="alcohol",data=df, line_kws={'color': 'grey'})
p.tick_params(labelsize=16)
p.set_xlabel(p.get_xlabel(),fontsize=22)
p.set_ylabel(p.get_ylabel(),fontsize=22)
plt.show()
def plot_correlationmatrix(train_df, threshold = 0):
"""Plot der Korrelationsmatrix des Datensatzes mit gegebener Schwelle
Args:
train_df (pandas.DataFrame): Datensatz
threshold (float): Schwelle, ab welchem Korrelationswert der Wert mit geplotet werden soll, Defaults ist 0.
"""
correlation_matrix = train_df.corr()
r = []
for w in np.round(correlation_matrix.values.reshape(-1),2):
if w > threshold or w < -threshold:
r.append(str(w))
else:
r.append("")
r = np.array(r).reshape(len(train_df.columns),len(train_df.columns))
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(correlation_matrix, annot=r, linewidths=.1,ax=ax,fmt="s",cmap=sns.diverging_palette(150, 275, s=80, l=55, n=9), vmin=-1, vmax=1)
def plot_metrics(y_test, y_pred, best_config, modelname="MODELNAME"):
"""Plot der Metriken Accuracy, Mean Absolut Error, Mean Squared Error
Args:
y_test (np.array): Labels des Testdatensatzes
y_pred (np.array): Vorhersagen des Modells
modelname (str): Modellname für die Plots, Defaults ist "MODELNAME"
"""
metric_list = np.asarray([[best_config["acc_train"], best_config["acc_val"], metrics.accuracy_score(np.round(y_pred),y_test)],
[best_config["mse_train"], best_config["mse_val"], metrics.mean_squared_error(y_pred,y_test),]
])
plt.figure(figsize=(8,6))
ax = plt.subplot(1, 1, 1)
p = sns.heatmap(metric_list, annot=True, linewidths=.5, cbar = False, annot_kws={"fontsize":18})
p.set_yticklabels(["Accuracy", "Mean Squared Error"], size = 16, rotation=0)
p.set_xticklabels(["Train", "Validation", "Test"], size = 16)
ax.set_title("Ergebnisse "+modelname,fontsize=20)
plt.tight_layout()
plt.show()
def plot_rfrfeatureimportance(rfr_model, train_df):
"""Plot der wichtigsten Features des Random Forest Regressor Modells
Args:
rfr_model (sklearn.ensemble.RandomForestRegressor): Random Forest Regressor Modell
train_df (pandas.DataFrame): Datenframe (benötigt für die Columns)
"""
index = np.argsort(rfr_model.feature_importances_)
performance = rfr_model.feature_importances_[index]
objects = train_df.drop('quality',axis=1).columns[index]
y_pos = np.arange(len(objects))
plt.figure(figsize=(12,8))
plt.barh(y_pos, performance, align='center', alpha=0.5)
plt.yticks(y_pos, objects, fontsize=14)
plt.xticks(fontsize=14)
plt.xlabel('feature_importances', fontsize=16)
plt.title('Feature importance Random Forest Regressor', fontsize=20)
plt.show()
def plot_rfr2d_2():
"""2D Plots des Random Forest Regressors
"""
df = pd.read_csv('results/train_conf_tree.csv')
df_min = df[df["min_samples_split"] == 2]
df_min = df_min[df_min["max_features"] =="log2"]
df_min=df_min.sort_values(by=['max_depth'])
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.set_title('Veränderung des MSE im Vergleich zur \n max Tief beim Random Forest', fontsize=20)
ax.plot(df_min["max_depth"], df_min["mse_val"], '-', label='Validation')
ax.plot(df_min["max_depth"], df_min["mse_train"], '-', label='Train')
ax2 = ax.twinx()
ax2.plot(df_min["max_depth"], df_min["time"], '-',label='time(s) for CV', color='black')
ax2.legend(loc=3)
ax.grid()
ax.set_xlabel("max_depth")
ax.set_ylabel("MSE")
ax2.set_ylabel("Time (s)")
df_min=df_min.sort_values(by=['mse_val'])
ax.plot(df_min["max_depth"][:1], df_min["mse_val"][:1], '', color = 'red', marker = 'o', label='min mse')
df_min=df_min.sort_values(by=['mse_train'])
ax.plot(df_min["max_depth"][:1], df_min["mse_train"][:1], '',color = 'red', marker = 'o')
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
plt.show()
df_ = df[df["max_features"] =="log2"]
df_=df_.sort_values(by=['min_samples_split'])
df_min = df_[df_["max_depth"] == 23]
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.plot(df_min["min_samples_split"], df_min["mse_val"], '-', label='Validation')
ax.plot(df_min["min_samples_split"], df_min["mse_train"], '-', label='Train')
ax.set_title('Veränderung des MSE im Vergleich zur \n min_samples_split beim Random Forest', fontsize=20)
ax2 = ax.twinx()
ax2.plot(df_min["min_samples_split"], df_min["time"], '-', label="time(s) for CV", color='black')
ax2.legend(loc=3)
ax.grid()
ax.set_xlabel("min_samples_split")
ax.set_ylabel("MSE")
ax.invert_xaxis()
ax2.set_ylabel("Time (s)")
df_min=df_min.sort_values(by=['mse_val'])
ax.plot(df_min["min_samples_split"][:1], df_min["mse_val"][:1], '' ,marker = 'o', color = 'red', label='min mse')
df_min=df_min.sort_values(by=['mse_train'])
ax.plot(df_min["min_samples_split"][:1], df_min["mse_train"][:1], '' ,marker = 'o',color = 'red')
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
plt.show()
def plot_histograms(y_test, y_pred, modelname="MODELNAME"):
"""Histogrammplots der wahren Values, der gerundeten Vorhersagen und der wahren Vorhersagen
Args:
y_test (np.array): Labels des Testdatensatzes
y_pred (np.array): Vorhersagen des Modells
modelname (str): Modellname für die Plots, Defaults ist "MODELNAME"
"""
plt.figure(figsize = (16, 5))
ax = plt.subplot(1, 3, 1)
p = sns.distplot(y_test)
p.tick_params(labelsize=12)
ax.set_ylabel("Number of Datapoints",fontsize=18)
ax.set_title("Ground Truth",fontsize=20)
ax = plt.subplot(1, 3, 2)
p = sns.distplot(np.round(y_pred))
p.tick_params(labelsize=12)
ax.set_xlabel("Quality",fontsize=18)
ax.set_ylabel("Number of Datapoints",fontsize=0)
ax.set_title("Rounded Prediction "+modelname,fontsize=20)
ax = plt.subplot(1, 3, 3)
p = sns.distplot(y_pred)
p.tick_params(labelsize=12)
ax.set_ylabel("Number of Datapoints",fontsize=0)
ax.set_title("Prediction "+modelname,fontsize=20)
plt.tight_layout()
plt.show()
def plot_confusion_matrix(y_test, y_pred, modelname="MODELNAME", datensatz="DATENSATZ"):
"""Plot der Confusion Matrix mit Recall und Precision
Args:
y_test (np.array): Labels des Testdatensatzes
y_pred (np.array): Vorhersagen des Modells
modelname (str): Modellname für die Plots, Defaults ist "MODELNAME"
datensatz (str): Datensatz für die Plots, Defaults ist "DATENSATZ"
"""
mat = metrics.confusion_matrix(y_test, np.round(y_pred))
cr = metrics.classification_report(y_test, np.round(y_pred),output_dict=True)
cr_list = []
for i in np.arange(3,10,1):
tmp_list = []
tmp_list.append(cr[str(i)]["precision"])
tmp_list.append(cr[str(i)]["recall"])
cr_list.append(tmp_list)
cr_list = np.asarray(cr_list)
plt.figure(figsize = (16, 7))
ax = plt.subplot(1, 2, 1)
p = sns.heatmap(mat, annot=True,fmt="d", linewidths=.5, cbar = False, annot_kws={"fontsize":14})
p.set_yticklabels(np.sort(np.unique(y_test)), size = 16)
p.set_xticklabels(np.sort(np.unique(y_test)), size = 16)
ax.set_xlabel("Rounded Prediction of Quality",fontsize=18)
ax.set_ylabel("Ground Truth Quality",fontsize=18)
ax.set_title("Confusion Matrix "+modelname+" "+datensatz,fontsize=20)
palette = sns.color_palette("coolwarm", as_cmap=False)
palette.reverse()
ax = plt.subplot(1, 2, 2)
p = sns.heatmap(cr_list, annot=True, cbar = False, linewidths=.5, annot_kws={"fontsize":14})
p.set_xticklabels(["Precision", "Recall"], size = 16)
p.set_yticklabels(np.sort(np.unique(y_test)), size = 0)
ax.set_title("Precision/Recall "+modelname+" "+datensatz,fontsize=20)
plt.tight_layout()
plt.show()
def plotEverything(df):
"""Plot aller Features des DataFrames
Args:
df (pandas.DataFrame): DatenFrame
"""
plt.figure(figsize = (25, 20))
plotnumber = 1
for col in df:
if plotnumber <= 12:
ax = plt.subplot(4, 3, plotnumber)
sns.distplot(df[col])
plt.xlabel(col, fontsize = 15)
plt.ylabel('')
plotnumber += 1
plt.tight_layout()
plt.show()
class CrossValidationValueRecorder:
"""Klasse um die Metriken der Crossvalidation zwischenzuspeichern
"""
def __init__(self):
"""Initialisierung der Klasse
"""
self.mse_val=[]
self.acc_val=[]
self.r2score_val=[]
self.mse_train=[]
self.acc_train=[]
self.r2score_train=[]
def Reset(self):
"""Reset der Klasse
"""
self.mse_val=[]
self.acc_val=[]
self.r2score_val=[]
self.mse_train=[]
self.acc_train=[]
self.r2score_train=[]
def UpdateConfig(self, train_config):
"""Updaten der Trainingsconfig
Args:
train_config (dict): Trainingsconfiguration
"""
train_config["mse_val"].append(np.mean(self.mse_val))
train_config["mse_train"].append(np.mean(self.mse_train))
train_config["acc_val"].append(np.mean(self.acc_val))
train_config["acc_train"].append(np.mean(self.acc_train))
train_config["r2score_val"].append(np.mean(self.r2score_val))
train_config["r2score_train"].append(np.mean(self.r2score_train))
def AddValidationMetric(self, y_val, y_pred):
"""Hinzufügen der Validationsmetriken
Args:
y_val (np.array): Labels des Validierungsdatensatzes
y_pred (np.array): Vorhersagen des Modells
"""
self.mse_val.append(metrics.mean_squared_error(y_val, y_pred))
self.acc_val.append(metrics.accuracy_score(np.rint(y_val).astype(int),np.rint(y_pred).astype(int)))
self.r2score_val.append(metrics.r2_score(y_val,y_pred))
def AddTrainMetric(self, y_train, y_pred):
"""Hinzufügen der Trainingsmetriken
Args:
y_train (np.array): Labels des Trainingsdatensatzes
y_pred (np.array): Vorhersagen des Modells
"""
self.mse_train.append(metrics.mean_squared_error(y_train, y_pred))
self.acc_train.append(metrics.accuracy_score(np.rint(y_train).astype(int),np.rint(y_pred).astype(int)))
self.r2score_train.append(metrics.r2_score(y_train,y_pred))
def GetMSE(self):
"""Hinzufügen der Trainingsmetriken
Returns:
np.mean(self.mse_val) (np.array): Durchschnitt des Mean Squared Errors auf den Validierungsdatensatz
"""
return np.mean(self.mse_val)
def ProductLength(hyperparameters):
"""Berechnung der Durchläufe eines Trainings
Args:
hyperparameters (list): Liste aller veränderlichen Hyperparameter
Returns:
length (int): Berechnete Anzahl Durchläufe eines Trainings
"""
length = 1
for p in hyperparameters:
sl = max(len(p),1)
length = length * sl
return length
def plot_logchanges(df):
"""Plot um die Veränderungen der Features durch das Logarithmieren aufzuzeigen
Args:
df (pandas.DataFrame): Datensatz
"""
plt.figure(figsize = (16, 10))
plotnumber = 1
for col in ["alcohol", "alcohol_Logarithm", "residual sugar", "residual sugar_Logarithm"]:
ax = plt.subplot(2, 2, plotnumber)
sns.distplot(df[col])
plt.xlabel(col, fontsize = 15)
plt.ylabel('')
plotnumber += 1
plt.show()
def plot_rfr3d():
"""3D Plots des Random Forest Regressors
"""
df = pd.read_csv("results/train_conf_tree.csv")
df_sqrt = df.loc[df['max_features'] == "sqrt"]
df_log2 = df.loc[df['max_features'] == "auto"]
fig = plt.figure(figsize=(16,10))
##first plot
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.set_title("MSE: sqrt")
ax.set_xlabel('max_depth')
ax.set_ylabel('min_samples_split')
ax.set_zlabel('mse')
plot_val = ax.plot_trisurf(df_sqrt["max_depth"].values, df_sqrt["min_samples_split"].values, df_sqrt["mse_val"],cmap='viridis',label='Validation')
plot_val._facecolors2d = plot_val._facecolor3d
plot_val._edgecolors2d = plot_val._edgecolor3d
plot_train = ax.plot_trisurf(df_sqrt["max_depth"].values, df_sqrt["min_samples_split"].values, df_sqrt["mse_train"],cmap='inferno',label="Train")
plot_train._facecolors2d = plot_train._facecolor3d
plot_train._edgecolors2d = plot_train._edgecolor3d
fig.colorbar(plot_train,location="bottom",shrink=0.7)
blue_patch = mpatches.Patch(color='tab:blue', label='Validation')
red_patch = mpatches.Patch(color='firebrick', label='Train')
ax.legend(handles=[blue_patch,red_patch])
# second plot
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.set_title("MSE: sqrt")
ax.set_xlabel('max_depth')
ax.set_ylabel('min_samples_split')
ax.set_zlabel('mse_vals')
plot = ax.plot_trisurf(df_sqrt["max_depth"].values, df_sqrt["min_samples_split"].values, df_sqrt["mse_val"],cmap='viridis', label="Validation")
plot._facecolors2d = plot._facecolor3d
plot._edgecolors2d = plot._edgecolor3d
plt.legend()
fig.colorbar(plot,location="bottom",shrink=0.7)
min_x = df_sqrt["max_depth"].iloc[np.argmin(df_sqrt["mse_val"])]
min_y = df_sqrt["min_samples_split"].iloc[np.argmin(df_sqrt["mse_val"])]
min_z = df_sqrt["mse_val"].iloc[np.argmin(df_sqrt["mse_val"])]
ax.plot(min_x,min_y,min_z,marker="o",c=plt.cm.coolwarm(1.))
def plot_svr_3d():
"""3D Plots des Support Vector Regressors
"""
df = pd.read_csv("results/train_conf_svr.csv")
df_std = df.loc[df['scaler'] == "StandardScaler()"]
df_minmax = df.loc[df['scaler'] == "MinMaxScaler()"]
df_std = df_std.loc[df_std['gamma'] == "0.31622776601683794"]
df_minmax = df_minmax.loc[df_minmax['gamma'] == "0.31622776601683794"]
fig = plt.figure(figsize=(16,10))
# first plot
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.set_title("MSE: StandardScaler")
ax.set_xlabel('C')
ax.set_ylabel('epsilon')
ax.set_zlabel('mse')
plot_val = ax.plot_trisurf(df_std["C"].values, df_std["epsilon"].values, df_std["mse_val"],cmap='viridis',label='Validation')
plot_val._facecolors2d = plot_val._facecolor3d
plot_val._edgecolors2d = plot_val._edgecolor3d
plot_train = ax.plot_trisurf(df_std["C"].values, df_std["epsilon"].values, df_std["mse_train"],cmap='inferno',label="Train")
plot_train._facecolors2d = plot_train._facecolor3d
plot_train._edgecolors2d = plot_train._edgecolor3d
fig.colorbar(plot_train,location="bottom",shrink=0.7)
blue_patch = mpatches.Patch(color='tab:blue', label='Validation')
red_patch = mpatches.Patch(color='firebrick', label='Train')
ax.legend(handles=[blue_patch,red_patch])
# second plot
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.set_title("MSE: StandardScaler")
ax.set_xlabel('C')
ax.set_ylabel('epsilon')
ax.set_zlabel('mse_vals')
plot = ax.plot_trisurf(df_std["C"].values, df_std["epsilon"].values, df_std["mse_val"].values,cmap='viridis', label="Validation")
plot._facecolors2d = plot._facecolor3d
plot._edgecolors2d = plot._edgecolor3d
plt.legend()
fig.colorbar(plot,location="bottom",shrink=0.7)
min_x = df_std["C"].iloc[np.argmin(df_std["mse_val"])]
min_y = df_std["epsilon"].iloc[np.argmin(df_std["mse_val"])]
min_z = df_std["mse_val"].iloc[np.argmin(df_std["mse_val"])]
ax.plot(min_x,min_y,min_z,marker="o",c=plt.cm.coolwarm(1.))
def plot_svr_feat_sel3d():
"""3D Plots des Support Vector Regressors mit Feature Selection
"""
df = pd.read_csv("results/train_conf_svr_feat_sel.csv")
df_minmax = df.loc[df['scaler'] == "MinMaxScaler()"]
df_minmax = df_minmax.loc[df_minmax['gamma'] == "scale"]
fig = plt.figure(figsize = (16,10))
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.set_title("MSE: MinMaxScaler")
ax.set_xlabel('C')
ax.set_ylabel('epsilon')
ax.set_zlabel('mse')
plot_val = ax.plot_trisurf(df_minmax["C"].values, df_minmax["epsilon"].values, df_minmax["mse_val"],cmap='viridis',label='Validation')
plot_val._facecolors2d = plot_val._facecolor3d
plot_val._edgecolors2d = plot_val._edgecolor3d
plot_train = ax.plot_trisurf(df_minmax["C"].values, df_minmax["epsilon"].values, df_minmax["mse_train"],cmap='inferno',label="Train")
plot_train._facecolors2d = plot_train._facecolor3d
plot_train._edgecolors2d = plot_train._edgecolor3d
fig.colorbar(plot_train,location="bottom",shrink=0.7)
blue_patch = mpatches.Patch(color='tab:blue', label='Validation')
red_patch = mpatches.Patch(color='firebrick', label='Train')
ax.legend(handles=[blue_patch,red_patch])
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.set_title("MSE: MinMaxScaler")
ax.set_xlabel('C')
ax.set_ylabel('epsilon')
ax.set_zlabel('mse_vals')
plot = ax.plot_trisurf(df_minmax["C"].values, df_minmax["epsilon"].values, df_minmax["mse_val"].values,cmap='viridis', label="Validation")
plot._facecolors2d = plot._facecolor3d
plot._edgecolors2d = plot._edgecolor3d
plt.legend()
fig.colorbar(plot,location="bottom",shrink=0.7)
min_x = df_minmax["C"].iloc[np.argmin(df_minmax["mse_val"])]
min_y = df_minmax["epsilon"].iloc[np.argmin(df_minmax["mse_val"])]
min_z = df_minmax["mse_val"].iloc[np.argmin(df_minmax["mse_val"])]
ax.plot(min_x,min_y,min_z,marker="o",c=plt.cm.coolwarm(1.))
def plot_rfr2d():
"""2D Plots des Random Forest Regressors
"""
df = pd.read_csv('results/train_conf_tree.csv')
df_min = df[df["min_samples_split"] == 2]
df_min = df_min[df_min["max_features"] =="log2"]
df_min=df_min.sort_values(by=['max_depth'])
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.set_title('Veränderung des MSE im Vergleich zur \n max Tief beim Random Forest', fontsize=20)
ax.plot(df_min["max_depth"], df_min["mse_val"], '-', label='Validation')
ax.plot(df_min["max_depth"], df_min["mse_train"], '-', label='Train')
ax2 = ax.twinx()
ax2.plot(df_min["max_depth"], df_min["time"], '-',label='time(s) for CV', color='black')
ax2.legend(loc=3)
ax.grid()
ax.set_xlabel("max_depth")
ax.set_ylabel("MSE")
ax2.set_ylabel("Time (s)")
df_min=df_min.sort_values(by=['mse_val'])
ax.plot(df_min["max_depth"][:1], df_min["mse_val"][:1], '', color = 'red', marker = 'o', label='min mse')
df_min=df_min.sort_values(by=['mse_train'])
ax.plot(df_min["max_depth"][:1], df_min["mse_train"][:1], '',color = 'red', marker = 'o')
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
ax.text(1.5, 0.5, 'Bei dem Plot wird die min_samples_split auf zwei gesetzt und den max_features auf log2,\nda so die besten Ergebnis erreicht werden. Der Plot zeigt die Veränderung des MSE in Abhängigkeit \nder maximale tief der Bäume. Es wird erkennbar, dass kaum eine Verbesserung festgestellt werden \nkann, bei einer tiefe > 20. Anhand der Zeit wird erkennbar das die Model bei einer maximale \nTief nicht mehr komplexer werde. Da die Bäume bereits die maximal aufgespannt sind. ',
verticalalignment='bottom', horizontalalignment='left',
transform=ax.transAxes,
color='black', fontsize=15)
plt.show()
df_ = df[df["max_features"] =="log2"]
df_=df_.sort_values(by=['min_samples_split'])
df_min = df_[df_["max_depth"] == 23]
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.plot(df_min["min_samples_split"], df_min["mse_val"], '-', label='Validation')
ax.plot(df_min["min_samples_split"], df_min["mse_train"], '-', label='Train')
ax.set_title('Veränderung des MSE im Vergleich zur \n min_samples_split beim Random Forest', fontsize=20)
ax.text(1.5, 0.5, 'Bei dem Plot wird die max_depth auf 23 gesetzt und den max_features auf log2,\nda so die besten Ergebnis erreicht werden. Der Plot zeigt die Veränderung des MSE in Abhängigkeit \nder min_samples_split. Es wird erkennbar, das ein maximale Aufteilung der Daten am sinnvollsten ist, \nalso min_samples_split =2',
verticalalignment='bottom', horizontalalignment='left',
transform=ax.transAxes,
color='black', fontsize=15)
ax2 = ax.twinx()
ax2.plot(df_min["min_samples_split"], df_min["time"], '-', label="time(s) for CV", color='black')
ax2.legend(loc=3)
ax.grid()
ax.set_xlabel("min_samples_split")
ax.set_ylabel("MSE")
ax.invert_xaxis()
ax2.set_ylabel("Time (s)")
df_min=df_min.sort_values(by=['mse_val'])
ax.plot(df_min["min_samples_split"][:1], df_min["mse_val"][:1], '' ,marker = 'o', color = 'red', label='min mse')
df_min=df_min.sort_values(by=['mse_train'])
ax.plot(df_min["min_samples_split"][:1], df_min["mse_train"][:1], '' ,marker = 'o',color = 'red')
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
plt.show()
def plot_svr2d():
"""2D Plots des Support Vector Regressors
"""
df = pd.read_csv('results/train_conf_svr.csv')
df_svr=df.sort_values(by=['gamma'])
df_svr = df_svr[df_svr["gamma"] == '0.31622776601683794']
df_svr = df_svr[df_svr["scaler"] == 'StandardScaler()']
df_svr = df_svr[df_svr["C"] < 1.43]
df_svr = df_svr[df_svr["C"] > 1.42]
df_svr=df_svr.sort_values(by=['epsilon'])
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.plot(df_svr["epsilon"], df_svr["mse_val"], '-', label=' Validation StandardScaler')
ax.plot(df_svr["epsilon"], df_svr["mse_train"], '-', label=' Train StandardScaler')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red')
ax2 = ax.twinx()
ax2.plot(df_svr["epsilon"], df_svr["time"], '-', label="StandardScaler: time(s) for CV", color='black')
df_svr=df.sort_values(by=['gamma'])
df_svr = df_svr[df_svr["gamma"] =='scale']
df_svr = df_svr[df_svr["scaler"] == 'MinMaxScaler()']
df_svr = df_svr[df_svr["C"] < 1.43]
df_svr = df_svr[df_svr["C"] > 1.42]
df_svr=df_svr.sort_values(by=['epsilon'])
ax.plot(df_svr["epsilon"], df_svr["mse_val"], '-', label=' Validation MinMaxScaler')
ax.plot(df_svr["epsilon"], df_svr["mse_train"], '-', label=' Train MinMaxScaler')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red', label='min mse')
ax.set_title('Veränderung des MSE im Vergleich zu \n Epsilon beim SVR', fontsize=20)
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
ax2.legend(bbox_to_anchor=(1.1, 0),loc='lower left')
ax.grid()
ax.set_xlabel("epsilon")
ax.set_ylabel("MSE")
ax2.set_ylabel("Time (s)")
plt.show()
df_svr = df[df["gamma"] =='0.31622776601683794']
df_svr = df_svr[df_svr["scaler"] == 'StandardScaler()']
df_svr = df_svr[df_svr["epsilon"] == 0.25]
df_svr=df_svr.sort_values(by=['C'])
fig = plt.figure(figsize = (8,5))
ax = fig.add_subplot(111)
ax.plot(df_svr["C"], df_svr["mse_val"], '-', label=' Validation StandardScaler')
ax.plot(df_svr["C"], df_svr["mse_train"], '-', label=' Train StandardScaler')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["C"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["C"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red')
ax2 = ax.twinx()
ax2.plot(df_svr["C"], df_svr["time"], '-', label="StandardScaler: time(s) for CV", color='black')
df_svr = df[df["gamma"] =='scale']
df_svr = df_svr[df_svr["scaler"] == 'MinMaxScaler()']
df_svr = df_svr[df_svr["epsilon"] == 0.25]
df_svr=df_svr.sort_values(by=['C'])
ax.plot(df_svr["C"], df_svr["mse_val"], '-', label=' Validation MinMaxScaler')
ax.plot(df_svr["C"], df_svr["mse_train"], '-', label=' Train MinMaxScaler')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["C"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["C"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red',label='min mse')
ax.set_title('Veränderung des MSE im Vergleich zu \n C beim SVR', fontsize=20)
ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
ax2.legend(bbox_to_anchor=(1.1, 0),loc='lower left')
ax.grid()
ax.set_xlabel("C")
ax.set_ylabel("MSE")
ax2.set_ylabel("Time (s)")
plt.show()
def plot_svr2d_feat_sel():
"""2D Plots des Support Vector Regressors mit Feature Selection
"""
df = pd.read_csv('results/train_conf_svr_feat_sel.csv')
df=df.sort_values(by=['mse_val'])
best_config=df.iloc[0].to_dict()
df_svr = df.sort_values(by=['gamma'])
df_svr = df_svr[df_svr["gamma"] =="scale"]
df_svr = df_svr[df_svr["scaler"] == 'StandardScaler()']
df_svr = df_svr[df_svr["C"] < 1.43]
df_svr = df_svr[df_svr["C"] > 1.42]
df_svr=df_svr.sort_values(by=['epsilon'])
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(df_svr["epsilon"], df_svr["mse_val"], '-', label=' Validation StandardScaler')
ax.plot(df_svr["epsilon"], df_svr["mse_train"], '-', label=' Train StandardScaler')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red')
df_svr=df.sort_values(by=['gamma'])
df_svr = df_svr[df_svr["gamma"] =="scale"]
df_svr = df_svr[df_svr["scaler"] == 'MinMaxScaler()']
df_svr = df_svr[df_svr["C"] < 1.43]
df_svr = df_svr[df_svr["C"] > 1.42]
df_svr=df_svr.sort_values(by=['epsilon'])
ax.plot(df_svr["epsilon"], df_svr["mse_val"], '-', label=' Validation MinMaxScaler')
ax.plot(df_svr["epsilon"], df_svr["mse_train"], '-', label=' Train MinMaxScaler')
ax.set_title('Veränderung des MSE im Vergleich zu \n Epsilon beim SVR mit Feature Selection', fontsize=20)
ax2 = ax.twinx()
ax2.plot(df_svr["epsilon"], df_svr["time"], '-', label="StandardScaler: time(s) for CV", color='black')
df_svr=df_svr.sort_values(by=['mse_val'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_val"][:1], '' ,marker = 'o', color = 'red')
df_svr=df_svr.sort_values(by=['mse_train'])
ax.plot(df_svr["epsilon"][:1], df_svr["mse_train"][:1], '' ,marker = 'o',color = 'red', label='min mse')
ax.legend(bbox_to_anchor=(1.1, 1), loc='upper left')
ax2.legend(bbox_to_anchor=(1.1, 0),loc='lower left')
ax.grid()
ax.set_xlabel("epsilon")
ax.set_ylabel("MSE")
ax2.set_ylabel("Time (s)")
plt.show()
csv = 'data/winequality-white.csv'
df = pd.read_csv(csv,sep=";")
Der Datensatz stammt aus dem Machine Learning Repository des UCI und wurde dort am 07.10.2009 eingetragen. Er enthält jeweils Daten für Weiswein und Rotwein des Vinho Verde, wobei für dieses Jupyter Notebook lediglich der Datensatz der Weisweine relevant ist.
Der Datensatz enthält 12 verschiedene Attribute, dabei wurden für diese Arbeit die ersten 11 Attribute zu Featuren deklariert und das letzte Attribut - Quality - zur Zielvariable. Für den Weiswein Datensatz gibt es 4898 Datenpunkte.
Anzumerken ist, dass die Qualität von Weinexperten evaluiert wurde. Dies bedeutet, dass die Weinqualität anhand subjektiven Wahrnehmungen der Experten bestimmt wurde.
Quelle:
[Cortez et al., 2009]
| Attribut | Erläuterung | Einheit |
|---|---|---|
| Fixed Acidity | Weinsäuren, welche in festem und nichtflüchtigen Zuständen vorkommen | g/dm3 |
| Volatile Acidity | Essigsäure, welche in hohen Konzentrationen zu einem Essiggeschmack führen | g/dm3 |
| Citric Acid | Zitronensäure, welche Weinen in geringer Quantität frische verleihen | g/dm3 |
| Residual Sugar | Zucker, welcher nach der Gärung verbleibt. | g/dm3 |
| Chlorides | Salzgehalt des Weins | g/dm3 |
| Free Sulfur Dioxide | Schwefeldioxid welches als gelöstes Gas und Bisulfit Ion vorkommen. Es verhindert mikrobielles Wachstum und die Oxidation des Weins |
g/dm3 |
| Total Sulfur Dioxide | Gesamtmenge des Schwefeldioxid in freier und gebundener Form. | g/dm3 |
| Density | Dichte | g/cm3 |
| pH | Gibt die Säure bzw. Base der Lösung an. 1 = sehr sauer bis 14 = sehr basisch |
Diskreter Wert zwischen 1-14 |
| Sulphates | Sulphate, die als Zusatz zum Wein gegeben werden und zum Gehalt der Schwefeloxiden beiträgt , welche antimikrobiell und antioxidativ wirken |
g/dm3 |
| Alcohol | Alkoholgehalt des Weins | Volumenprozent |
| Quality | Median der Weinqualität aus 3 Evaluationen gegeben von Weinexperten 1 = Schlecht 10 = Sehr Gut |
Diskreter Wert zwischen 1-10 |
df
| fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol | quality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 7.0 | 0.27 | 0.36 | 20.7 | 0.045 | 45.0 | 170.0 | 1.00100 | 3.00 | 0.45 | 8.8 | 6 |
| 1 | 6.3 | 0.30 | 0.34 | 1.6 | 0.049 | 14.0 | 132.0 | 0.99400 | 3.30 | 0.49 | 9.5 | 6 |
| 2 | 8.1 | 0.28 | 0.40 | 6.9 | 0.050 | 30.0 | 97.0 | 0.99510 | 3.26 | 0.44 | 10.1 | 6 |
| 3 | 7.2 | 0.23 | 0.32 | 8.5 | 0.058 | 47.0 | 186.0 | 0.99560 | 3.19 | 0.40 | 9.9 | 6 |
| 4 | 7.2 | 0.23 | 0.32 | 8.5 | 0.058 | 47.0 | 186.0 | 0.99560 | 3.19 | 0.40 | 9.9 | 6 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 4893 | 6.2 | 0.21 | 0.29 | 1.6 | 0.039 | 24.0 | 92.0 | 0.99114 | 3.27 | 0.50 | 11.2 | 6 |
| 4894 | 6.6 | 0.32 | 0.36 | 8.0 | 0.047 | 57.0 | 168.0 | 0.99490 | 3.15 | 0.46 | 9.6 | 5 |
| 4895 | 6.5 | 0.24 | 0.19 | 1.2 | 0.041 | 30.0 | 111.0 | 0.99254 | 2.99 | 0.46 | 9.4 | 6 |
| 4896 | 5.5 | 0.29 | 0.30 | 1.1 | 0.022 | 20.0 | 110.0 | 0.98869 | 3.34 | 0.38 | 12.8 | 7 |
| 4897 | 6.0 | 0.21 | 0.38 | 0.8 | 0.020 | 22.0 | 98.0 | 0.98941 | 3.26 | 0.32 | 11.8 | 6 |
4898 rows × 12 columns
In der Betrachtung der Features im Pairplot sind keine generellen Aufteilungen zu erkennen. Im Vergleich zur Zielvariable - der Weinqualität("quality") - sieht man bei den meisten Features keine großartigen Verschiebungen. Beim Feature Alkohol("alcohol") sieht man eine leichte Verschiebung der Normalverteilungen pro Weinqualität. Es scheint so, als würde ein größerer Alkoholwert eine bessere Weinqualität ausmachen.
Desweiteren sind starke Ausreißer zu erkennen.
sns.pairplot(df, hue="quality", palette = sns.color_palette("tab10", n_colors=7), plot_kws={'alpha': 1})
<seaborn.axisgrid.PairGrid at 0x272db9d7eb0>
Die folgenden Grafiken verdeutlichen, dass die starken Ausreißer teilweise einen vielfach größeren Wert besitzen als die meisten ihres Features. Gerade bei dem Salzgehalt("chlorides"), dem Zucker nach der Gärung("residual sugar") und dem Schwefeldioxid("free sulfur dioxide") ist dies sehr gut zu erkennen. Da diese Werte höchst unwahrscheinlich sind und höchstwahrscheinlich Mess- oder Produktionsfehler darstellen, sollten diese vom Datensatz entfernt werden, da einige Algorithmen stark durch Ausreißer beeinflusst werden.
Ebenso ist anzumerken, dass die Zielvariable höchst unausgeglichen verteilt ist. Es ist deutlich zu erkennen, dass die Klasse $6$ am häufigsten vorkommt und fast gleich viel Datenpunkte beinhaltet wie die zweit und dritthäufigste Klassen $5$ und $7$ zusammen. Dazu sind die Klassen $\leq 4$ und $\geq 8$ fast gar nicht vertreten.
plotEverything_2(df)
Wie in der oberen Grafik zu sehen ist, befinden sich im Datensatz einige Ausreißer. Zum Detektieren und Entfernen von Ausreißern werden meist die Standard Deviation Methode und die IQR-Methode verwendet.
Quelle:
Bei der Interquartile Range Methode, kurz $\mathit{IQR}$, wird zunächst der Wert des $\mathit{IQR}$ bestimmt, welcher durch die Differenz des 3. und 1. Quartils berechnet wird. Als Ausreißer werden in der Regel Datenpunkte mit Werten von $1.5*\mathit{IQR}$ oberhalb des oberen Quartils oder unterhalb des unteren Quartils bezeichnet.
Quellen:
def remOutliers_IQR(x):
"""Entfernung von Ausreißern im Datensatz mit der IQR-Methode
Args:
x (pandas.DataFrame): DatenFrame ohne Zielvariable
Returns:
x (pandas.DataFrame): DatenFrame ohne Ausreißer
"""
print("Entfernung von Ausreißern mit der IQR Methode\nShape des Datenframes vor der Anwendung",x.shape)
Q1 = x.quantile(0.25)
Q3 = x.quantile(0.75)
IQR = Q3 - Q1
x = x[~((x < (Q1 - 1.5 * IQR)) |(x > (Q3 + 1.5 * IQR))).any(axis=1)]
print("Shape des Datenframes nach der Anwendung",x.shape)
return x
iqr_df = remOutliers_IQR(df.drop("quality",axis=1))
iqr_df = pd.merge(iqr_df, df["quality"], left_index=True, right_index=True)
iqr_df.reset_index(drop=True, inplace=True)
Entfernung von Ausreißern mit der IQR Methode Shape des Datenframes vor der Anwendung (4898, 11) Shape des Datenframes nach der Anwendung (4015, 11)
Mit der $\mathit{IQR}$-Methode werden $883$ Datenpunkte als Ausreißer definiert.
sns.pairplot(iqr_df, hue="quality", palette = sns.color_palette("tab10", n_colors=7), plot_kws={'alpha': 1})
<seaborn.axisgrid.PairGrid at 0x272eb91a460>
plotEverything_2(iqr_df)
Bei der Standard Deviation Methode werden mit Hilfe der Standardabweichung und dem Mean Ausreißer identifiziert. Dabei wird der Z-Score wie folgt berechnet:
$$z =\frac{x_i-\mu}{\sigma}$$In einer Normalverteilung ist davon auszugehen, dass $\mathit{3*\sigma}\;\;$ 99.73% aller Werte enthalten sind. Werte darüber werden in der Regel als Ausreißer angesehen.
Quellen:
def remOutliers_ZScore(x):
"""Entfernung von Ausreißern im Datensatz mit der Standard Deviation Methode
Args:
x (pandas.DataFrame): DatenFrame ohne Zielvariable
Returns:
x (pandas.DataFrame): DatenFrame ohne Ausreißer
"""
print("Entfernung von Ausreißern mit der Z-Score Methode\nShape des Datenframes vor der Anwendung",x.shape)
z = np.abs(stats.zscore(x))
x = x[(z < 3).all(axis=1)]
print("Shape des Datenframes nach der Anwendung",x.shape)
return x
zscore_df = remOutliers_ZScore(df.drop("quality",axis=1))
zscore_df = pd.merge(zscore_df, df["quality"], left_index=True, right_index=True)
zscore_df.reset_index(drop=True, inplace=True)
Entfernung von Ausreißern mit der Z-Score Methode Shape des Datenframes vor der Anwendung (4898, 11) Shape des Datenframes nach der Anwendung (4502, 11)
Mit der Standard Deviation Methode werden $396$ Datenpunkte als Ausreißer definiert.
plotEverything_2(zscore_df)
sns.pairplot(zscore_df, hue="quality", palette = sns.color_palette("tab10", n_colors=7), plot_kws={'alpha': 1})
<seaborn.axisgrid.PairGrid at 0x272f7758250>
Sowohl bei der Standard Deviation Methode, als auch bei der $\mathit{IQR}$-Methode wurden die starken Ausreißer im Datensatz erkannt und eliminiert. Die $\mathit{IQR}$-Methode hat 883 Datenpunkte eliminiert und den Datensatz stärker beschnitten als die Standard Deviation Methode mit 396 Datenpunkten. Aus den Grafiken ist zu erkennen, dass beide Methoden die Ausreißer effektiv beseitigen und beide Methoden eine legitime Wahl für die Entfernung der Ausreißer darstellen. Für den weiteren Verlauf wurde sich für die Standard Deviation Methode entschieden, da dieser alle Ausreißer erkennt und weniger Datenpunkte als die $\mathit{IQR}$-Methode entfernt.
df = zscore_df
Für einige Machine Learning Algorithmen ist es vorteilhaft, wenn Features einer Normalverteilung folgen. Dies führt dazu, dass die Kostenfunktion den Fehler der Vorhersagen besser minimiert.
Wie in der Grafik zu sehen, sind einige Features, wie zum Beispiel das Feature "residual sugar", nicht normalverteilt und stark in eine Richtung verzerrt. Durch das Logarithmieren dieser Features lassen sich die Datenpunkte mehr zu einer Normalverteilung transformieren. Diese Transformation werden für die Features "residual sugar" und "alcohol" angewendet.
Quellen:
plotEverything_2(df)
for name in ["alcohol", "residual sugar"]:
df[name+'_Logarithm'] = df[name].apply(lambda x : np.log(x))
Nach der Logarithmierung gleichen die Features eher einer Normalverteilung.
plot_logchanges(df)
Die Aufteilung der Daten in Trainings- und Testdatensätze wird mit dem Train_test_split von Scikit-Learn durchgeführt. Es werden $25\%$ der Daten dem Testdatensatz zugesprochen. Dieser Datensatz wird während dem gesamten Training nicht beachtet. Anhand dem Testdatensatz werden am Ende das optimierte Modell auf die während dem Training ungesehenen Daten evaluiert. Die Aufteilung wird mit dem oben definierten Seed durchgeführt, um die Ergebnisse reproduzierbar zu machen. Die Daten werden während der Aufteilung gemischt und statifiziert getrennt. Stratifizierte Aufteilung bedeutet, dass sich sowohl in dem Trainings- als auch im Testdatensatz die gleiche prozentuale Aufteilung der Zielvariable Weinqualität befinden.
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(df.index, df['quality'], test_size=0.25, random_state=seed, shuffle=True, stratify=df['quality'])
train_df = df.iloc[X_train]
test_df = df.iloc[X_test]
train_df
| fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol | quality | alcohol_Logarithm | residual sugar_Logarithm | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2181 | 7.0 | 0.16 | 0.26 | 7.3 | 0.047 | 30.0 | 220.0 | 0.99622 | 3.38 | 0.58 | 10.1 | 6 | 2.312535 | 1.987874 |
| 3927 | 7.2 | 0.22 | 0.35 | 5.5 | 0.054 | 37.0 | 183.0 | 0.99474 | 3.08 | 0.50 | 10.3 | 5 | 2.332144 | 1.704748 |
| 728 | 8.1 | 0.17 | 0.44 | 14.1 | 0.053 | 43.0 | 145.0 | 1.00060 | 3.28 | 0.75 | 8.8 | 8 | 2.174752 | 2.646175 |
| 4173 | 6.4 | 0.24 | 0.27 | 1.5 | 0.040 | 35.0 | 105.0 | 0.98914 | 3.13 | 0.30 | 12.4 | 6 | 2.517696 | 0.405465 |
| 2726 | 6.0 | 0.32 | 0.30 | 1.3 | 0.025 | 18.0 | 112.0 | 0.98802 | 3.07 | 0.64 | 13.3 | 7 | 2.587764 | 0.262364 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 2406 | 6.8 | 0.19 | 0.23 | 5.1 | 0.034 | 71.0 | 204.0 | 0.99420 | 3.23 | 0.69 | 10.1 | 5 | 2.312535 | 1.629241 |
| 2260 | 6.3 | 0.18 | 0.22 | 1.5 | 0.043 | 45.0 | 155.0 | 0.99238 | 3.19 | 0.48 | 10.2 | 5 | 2.322388 | 0.405465 |
| 1927 | 7.1 | 0.22 | 0.32 | 16.9 | 0.056 | 49.0 | 158.0 | 0.99980 | 3.37 | 0.38 | 9.6 | 6 | 2.261763 | 2.827314 |
| 2855 | 5.9 | 0.33 | 0.32 | 8.1 | 0.038 | 9.0 | 34.0 | 0.99110 | 3.22 | 0.36 | 12.7 | 7 | 2.541602 | 2.091864 |
| 617 | 6.8 | 0.25 | 0.34 | 14.0 | 0.032 | 47.0 | 133.0 | 0.99520 | 3.37 | 0.50 | 12.2 | 7 | 2.501436 | 2.639057 |
3376 rows × 14 columns
test_df
| fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol | quality | alcohol_Logarithm | residual sugar_Logarithm | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2632 | 6.2 | 0.21 | 0.26 | 13.10 | 0.050 | 59.0 | 150.0 | 0.99772 | 3.31 | 0.46 | 9.0 | 5 | 2.197225 | 2.572612 |
| 2665 | 7.1 | 0.27 | 0.28 | 1.25 | 0.023 | 3.0 | 89.0 | 0.98993 | 2.95 | 0.30 | 11.4 | 4 | 2.433613 | 0.223144 |
| 2150 | 7.6 | 0.48 | 0.37 | 1.20 | 0.034 | 5.0 | 57.0 | 0.99256 | 3.05 | 0.54 | 10.4 | 3 | 2.341806 | 0.182322 |
| 3701 | 7.4 | 0.16 | 0.27 | 15.50 | 0.050 | 25.0 | 135.0 | 0.99840 | 2.90 | 0.43 | 8.7 | 7 | 2.163323 | 2.740840 |
| 3104 | 7.7 | 0.46 | 0.18 | 3.30 | 0.054 | 18.0 | 143.0 | 0.99392 | 3.12 | 0.51 | 10.8 | 6 | 2.379546 | 1.193922 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 1017 | 6.3 | 0.23 | 0.21 | 5.10 | 0.035 | 29.0 | 142.0 | 0.99420 | 3.36 | 0.33 | 10.1 | 7 | 2.312535 | 1.629241 |
| 583 | 6.2 | 0.24 | 0.29 | 13.30 | 0.039 | 49.0 | 130.0 | 0.99520 | 3.33 | 0.46 | 11.0 | 8 | 2.397895 | 2.587764 |
| 1664 | 7.0 | 0.24 | 0.25 | 1.70 | 0.042 | 48.0 | 189.0 | 0.99200 | 3.25 | 0.42 | 11.4 | 6 | 2.433613 | 0.530628 |
| 1112 | 6.8 | 0.18 | 0.37 | 1.50 | 0.027 | 37.0 | 93.0 | 0.99200 | 3.30 | 0.45 | 10.8 | 6 | 2.379546 | 0.405465 |
| 4416 | 6.0 | 0.35 | 0.46 | 0.90 | 0.033 | 9.0 | 65.0 | 0.98934 | 3.24 | 0.35 | 12.1 | 4 | 2.493205 | -0.105361 |
1126 rows × 14 columns
train_df.to_csv("data/train_weisswein_preprocessed.csv",sep=';',index=False)
test_df.to_csv("data/test_weisswein_preprocessed.csv",sep=';',index=False)
Mit Hilfe der Korrelationsmatrix lassen sich Korrelationen zwischen den Features und den Features mit der Zielvariablen darstellen. Mit Blick auf die Zielvariable "quality" erkennt man eine moderate Korrelation zu den Features "alcohol", "density" und "chlorides". Daraus lässt sich herleiten, dass diese Features einen höheren Einfluss auf die Vorhersage unserer Modelle nehmen werden. Allerdings sollte man bei einigen Algorithmen Korrelationen zwischen Features vermeiden. Multikollinearität zwischen Features macht die Schätzung des Regressionskoeffizienten instabil und sie wird ungenauer.
Quellen:
correlation_matrix = train_df.corr()
correlation_matrix
| fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol | quality | alcohol_Logarithm | residual sugar_Logarithm | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| fixed acidity | 1.000000 | -0.046495 | 0.289624 | 0.076430 | 0.082431 | -0.026143 | 0.067661 | 0.253869 | -0.394528 | -0.028987 | -0.113803 | -0.088480 | -0.109349 | 0.059403 |
| volatile acidity | -0.046495 | 1.000000 | -0.160668 | 0.057252 | 0.017185 | -0.071575 | 0.098533 | -0.010702 | -0.033185 | -0.035661 | 0.084213 | -0.128470 | 0.070793 | 0.101971 |
| citric acid | 0.289624 | -0.160668 | 1.000000 | 0.087733 | 0.036582 | 0.127887 | 0.124891 | 0.138359 | -0.152483 | 0.067582 | -0.060464 | 0.006184 | -0.062888 | 0.072569 |
| residual sugar | 0.076430 | 0.057252 | 0.087733 | 1.000000 | 0.255597 | 0.343204 | 0.410051 | 0.838573 | -0.195250 | -0.018294 | -0.478968 | -0.110791 | -0.493436 | 0.938769 |
| chlorides | 0.082431 | 0.017185 | 0.036582 | 0.255597 | 1.000000 | 0.121873 | 0.332957 | 0.469893 | -0.031905 | 0.079481 | -0.518506 | -0.313374 | -0.521323 | 0.223371 |
| free sulfur dioxide | -0.026143 | -0.071575 | 0.127887 | 0.343204 | 0.121873 | 1.000000 | 0.622337 | 0.343954 | -0.008545 | 0.079742 | -0.269085 | 0.015068 | -0.274254 | 0.347809 |
| total sulfur dioxide | 0.067661 | 0.098533 | 0.124891 | 0.410051 | 0.332957 | 0.622337 | 1.000000 | 0.547046 | 0.024808 | 0.159143 | -0.461150 | -0.171947 | -0.466925 | 0.422419 |
| density | 0.253869 | -0.010702 | 0.138359 | 0.838573 | 0.469893 | 0.343954 | 0.547046 | 1.000000 | -0.081709 | 0.092243 | -0.815035 | -0.318027 | -0.820908 | 0.772972 |
| pH | -0.394528 | -0.033185 | -0.152483 | -0.195250 | -0.031905 | -0.008545 | 0.024808 | -0.081709 | 1.000000 | 0.169218 | 0.101405 | 0.100540 | 0.110064 | -0.170065 |
| sulphates | -0.028987 | -0.035661 | 0.067582 | -0.018294 | 0.079481 | 0.079742 | 0.159143 | 0.092243 | 0.169218 | 1.000000 | -0.046919 | 0.036664 | -0.044199 | -0.021165 |
| alcohol | -0.113803 | 0.084213 | -0.060464 | -0.478968 | -0.518506 | -0.269085 | -0.461150 | -0.815035 | 0.101405 | -0.046919 | 1.000000 | 0.452146 | 0.998319 | -0.410607 |
| quality | -0.088480 | -0.128470 | 0.006184 | -0.110791 | -0.313374 | 0.015068 | -0.171947 | -0.318027 | 0.100540 | 0.036664 | 0.452146 | 1.000000 | 0.447331 | -0.069520 |
| alcohol_Logarithm | -0.109349 | 0.070793 | -0.062888 | -0.493436 | -0.521323 | -0.274254 | -0.466925 | -0.820908 | 0.110064 | -0.044199 | 0.998319 | 0.447331 | 1.000000 | -0.423633 |
| residual sugar_Logarithm | 0.059403 | 0.101971 | 0.072569 | 0.938769 | 0.223371 | 0.347809 | 0.422419 | 0.772972 | -0.170065 | -0.021165 | -0.410607 | -0.069520 | -0.423633 | 1.000000 |
plot_correlationmatrix(train_df, threshold = 0.3)
correlation_matrix['quality'].sort_values(ascending=False)
quality 1.000000 alcohol 0.452146 alcohol_Logarithm 0.447331 pH 0.100540 sulphates 0.036664 free sulfur dioxide 0.015068 citric acid 0.006184 residual sugar_Logarithm -0.069520 fixed acidity -0.088480 residual sugar -0.110791 volatile acidity -0.128470 total sulfur dioxide -0.171947 chlorides -0.313374 density -0.318027 Name: quality, dtype: float64
Zur Minimierung des Problems der Multikollinearität werden einige Features eliminiert. Man erkennt, dass das Feature "alcohol", bzw dessen logarithmierte Form die größte Korrelation zur Zielvariable besitzt. Als Schwellenwert der Korrelation zwischen Features wurde 0.3 gewählt. Durch die Wahl des Features "alcohol" elimieren wir dadurch die Features "total sulfure dioxide", "residual sugar" und dessen logarithmierte Form, "chlorides" und "density". Die nächstgrößte Korrelation der verbleibenden Features finde sich in "volatile acidity". Dieses Feature besitzt keine Korrelationen über unserem Schwellenwert, wodurch keine anderen Features eliminiert werden. Nach diesem Schema wurden die Features "pH", "sulphates" und "citric acid" gewählt und das Feature "fixed acidity" ebenfalls eliminiert.
Daraus erfolgt die Liste folgender Features für den Datensatz der Feature Selection:
Im Laufe des Projekts wird sowohl ein SVR Modell mit dem gesamten Datensatz und ein SVR Modell mit dem Datensatz der Feature Selection trainiert und anschließend evaluiert.
plot_correlatedfeatures()
Eine mäßig-starke Korrelation hat das Feature Alkohol zur Zielvariablen Qualität. Dies wirkt sich positiv auf das spätere Modell aus, da das Feature dadurch einen besseren Informationsgewinn hat.
sns.lmplot(x="quality", y="alcohol", data=df, line_kws={'color': 'grey'})
<seaborn.axisgrid.FacetGrid at 0x272ff206cd0>
def get_datasets(logarithm = False, feature_selection = False):
"""Laden der Datensätze
Args:
logarithm (bool): Logarithmierte Features anstelle der normalen verwenden
feature_selection (bool): Nur selektierte Features des Datensatzes laden
Returns:
train_df (pd.DataFrame): Trainingsdatensatz
test_df (pd.DataFrame): Testdatensatz
"""
train_df = pd.read_csv('data/train_weisswein_preprocessed.csv',sep=";")
test_df = pd.read_csv('data/test_weisswein_preprocessed.csv',sep=";")
if feature_selection:
columns = ["alcohol", "alcohol_Logarithm", "pH", "volatile acidity", "sulphates", "citric acid", "quality"]
if logarithm:
columns.remove("alcohol")
else:
columns.remove("alcohol_Logarithm")
else:
columns = list(train_df.columns)
if logarithm:
columns.remove("alcohol")
columns.remove("residual sugar")
else:
columns.remove("alcohol_Logarithm")
columns.remove("residual sugar_Logarithm")
return train_df[columns], test_df[columns]
In Machine Learning ist die Skalierung von Daten ein wichtiger Schritt. Einige Machine Learning Algorithmen performen besser, wenn sie sie eine ähnliche Größenordnung der Einheiten vorweisen. Dies liegt an der Schrittgröße, die im Minimierungsverfahren gebraucht wird. Bei unterschiedlicher Größenordnung würde man pro Einheit eine Schrittgröße benötigen. Als Skaliermethoden werden meist eine MinMax-Skalierung oder eine Skalierung anhand der Standardabweichung bevorzugt angewandt. Dabei bietet es sich an, die Funktionen StandardScaler() und MinMaxScaler() von Scikit-Learn zu verwenden. Diese zwei Skaliermethoden werden im Laufe des Jupyter Notebooks verglichen, indem sie für den Support Vector Regressor als Hyperparameter mitgegeben werden. Beim Random Forest Regressor macht eine Skalierung keinen Sinn, da dies kein distanzbasiertes Modell ist.
Die Skalierung wird pro Training in der Kreuzvalidierung durchgeführt. So wird bei jedem neuen Training zunächst die Scikit-Learn-Funktionen mit den Trainingsdaten trainiert und anschließend der Trainings- und Validierungsdatensatz mit den Scikit-Learn-Funktionen skaliert.
Quellen:
Da die Aufgabe - die Bestimmung der Weinqualität - eine ordinale Regression ist, werden Regressionsalgorithmen benötigt.
Eins der Machine Learning Modelle, welche wir verwenden ist ein Support Vektor Regressor(SVR). Es ist eine Version, der in der Vorlesung behandelten Support Vektor Maschine. Diese Version wird bei Regressionsproblemen angewandt.
Mit 10.000 Datenpunkte gilt ist Datensatz recht klein und somit kann die libsvm Implementation ohne Bedenken verwendet werden. Diese Implementierung bietet im Gegensatz zur linearen SVR verschiedene Kernel. Bei größeren Datensätzen mit mehreren zehntausend Datenpunkten steigt die Komplexität mehr als quadratisch an.
Da die Scikit-Learn-Implementierung von SVR eine Vielzahl an Parametern besitzt, müssen die korrekten Parameter zunächst mit einem Trainingprozess bestimmt werden.
Die Suche der besten Parameterkombination erfolgt mittels Gridsearch. Da Gridsearch eine Komplexität von $\mathcal{O}(k^n)$ Möglichkeiten besitzt, muss vorab eine Auswahl getroffen werden, welche Parameter ausführlich optimiert werden.
SVR selbst besitzt nur zwei freie Parameter.
Nach vorherigen Tests stellten sich die Daten nicht als linear seperabel heraus. Diese Implemenation verwendet den Radial Bias Kernel, kurz rbf, da dieser gute Ergebnisse lieferte. Es wurde sich gegen den Polynomial Kernel entschieden, da dieser schlechtere Ergebnisse bei erhöhter Laufzeit lieferte.
Der Radial Bias Kernel besitzt eine zusätliche Variable Gamma, welche optimiert werden kann. Standardmäßig wird Gamma mit Hilfe der Trainingsdaten bestimmt.
In den neueren Versionen ist der Standardwert für Gamma auf "scale" gesetzt.
Ein weiterer Optimierungsparameter ist das oben genannte Skalieren. Dies wird mittels einer Pipeline umgesetzt.
Daraus ergeben sich vier Parameter welche mit Hilfe des Gridsearchalgorithmus optimiert werden müssen. Die Funktion kann ebenso mit anderen Kerneln verwendet werden, zum Beispiel "sigmoid", "linear" oder "poly". Der Polynomial Kernel besitzt einen eigenen Parameter Grad("degree"), welche anstelle von Gamma optimiert werden würde.
Quellen: https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html
def SupportVectorRegressor_train(X, y, cross_validation = False, hyperparameter = None, n_splits = 3, n_repeats = 1, seed = 42, kernel = "rbf", test_for_professor = False):
"""Trainiert ein SVR Model mit gegebenen Hyperparametern.
Falls Cross Validation auf Wahr gesetzt wurde, werden SVR Modelle mit Hilfe einer
Datensatzaufteilung durch KFold trainiert um optimale Hyperparameter zu bestimmen.
Args:
X (np.array): Features des Trainingsdatensatzes
y (np.array): Labels des Trainingsdatensatz
cross_validation (bool): Ob Cross Validation verwendet werden soll um Hyperparameter zu bestimmen,
ansonsten wird ein Modell mit den übergebenen Hyperparametern trainiert. Defaults ist False
hyperparameter (dict oder None): Übergabe der Hyperparameter für das Modell bei cross_validation = True. Defaults ist None
n_splits (int): Anzahl an Spaltungen für Cross Validation. Defaults ist 3
n_repeats (n_repeats): Wiederholungen der Cross Validation. Defaults ist 1
seed (int): Seed für den KFold Algorithmus. Defaults ist 42
kernel (str): Kernel, welcher von dem SVR Modell verwendet werden soll. Defaults ist "rbf"
test_for_professor (bool): Test für den Professor/Kommilitonen um schneller zu trainieren. Defaults ist False
Returns:
cross_validation == True:
train_config (dict): Ein Array von Objekten, welcher die Hyperparameter und Metriken des Trainings beinhaltet
cross_validation == False:
model (object): Das trainierte Model
Raise:
ValueError: Falls beim Trainieren eines Modells in dem Hyperparameter Dictionary ein falscher Wert übergeben wurde.
"""
if cross_validation:
zeitanfang = time.time()
train_config = {
"kernel":[],
"epsilon":[],
"C":[],
"gamma":[],
"degree":[],
"r2score_train":[],
"mse_train":[],
"acc_train":[],
"r2score_val":[],
"mse_val":[],
"acc_val":[],
"scaler":[],
"time":[],
}
min_samples_split=np.unique(np.round(np.logspace(1, 6, num=10, base=2)).astype(int))
# Default Values, please change
epsilon = np.arange(0.05, 0.5, 0.05)
C = np.logspace(-1.5, 1.5, num=30, base=10)
# Manual gamma settings, with auto and scale as the first parameters
# scale uses 1 / (n_features * X.var())
# auto uses 1 / n_features.
gamma = np.logspace(-2, 0, num=5, base=10)
gamma = ["scale", "auto"]+list(gamma)
# Degree range for use with the poly kernel. The second variable in range is exclusive.
degree = range(1,4)
if test_for_professor:
# Test values to test functionality
epsilon = np.arange(0.05, 0.1, 0.05)
C = np.logspace(0, 0.5, num=5, base=10)
gamma = [0.31622776601683794]
degree = [3]
# Only the poly kernel uses the degree parameter, so for all other kernels it can be set to one element to reduce permutations.
if kernel is not "poly":
degree=[0]
# linear does not use the gamma parameter, so it can be reduced to one entry to reduce permutations.
if kernel is "linear":
gamma = ["scale"]
scaler = [StandardScaler(),MinMaxScaler()]
cvvr = CrossValidationValueRecorder()
rkf = RepeatedKFold(n_splits=n_splits, n_repeats=n_repeats, random_state=seed)
# Calculating the amount of the length of the cartesian product
num_train = ProductLength([epsilon, C, gamma, scaler, degree])
# Running the cross validation
for i,(e,c,g,s,d) in enumerate(itertools.product(epsilon,C,gamma,scaler,degree)):
print(f'{i+1:5d}/{num_train} {e:.3f} {c:.3f} {g} {str(s):16}', d, end='')
# Insert model specific values
train_config["epsilon"].append(e)
train_config["C"].append(c)
train_config["gamma"].append(g)
train_config["scaler"].append(s)
train_config["degree"].append(d)
train_config["kernel"].append(kernel)
cvvr.Reset()
trainingTimeBegin = time.time()
for train_index, val_index in rkf.split(X):
X_train, X_val = X[train_index], X[val_index]
y_train, y_val = y[train_index], y[val_index]
svr = SVR(kernel=kernel, C=c, epsilon=e, gamma=g, degree=d)
pipe = Pipeline([('scaler', s), ('svc', svr)])
pipe.fit(X_train,y_train)
model = pipe.fit(X_train, y_train)
#val
y_pred = model.predict(X_val)
cvvr.AddValidationMetric(y_val, y_pred)
#Train
y_pred = model.predict(X_train)
cvvr.AddTrainMetric(y_train, y_pred)
trainingTime = time.time()-trainingTimeBegin
train_config["time"].append(trainingTime)
print(' ->',cvvr.GetMSE())
# Add Scores to evaluate
cvvr.UpdateConfig(train_config)
processingTime = time.time()-zeitanfang
print(f"Time Taken {processingTime:.3f}s")
return train_config
else:
if (hyperparameter['gamma'] == "auto" or hyperparameter["gamma"] == "scale"):
gamma = hyperparameter['gamma']
else:
gamma = float(hyperparameter['gamma'])
svr = SVR(kernel = kernel, degree = hyperparameter['degree'], C = hyperparameter['C'], epsilon = hyperparameter['epsilon'], gamma = gamma)
if hyperparameter['scaler'] == "StandardScaler()":
scaler = StandardScaler()
elif hyperparameter['scaler'] == "MinMaxScaler()":
scaler = MinMaxScaler()
else:
raise ValueError(f"Scaler not found please insert \"StandardScaler()\" or \"MinMaxScaler()\" ")
pipe = Pipeline([('scaler', scaler), ('svc', svr)])
model = pipe.fit(X, y)
return model
Entscheidungsbäume sind in der Lage sich sehr gut auf einen Datensatz anzupassen, allerdings weisen sie sehr oft eine hohe Varianz auf und neigen daher sehr stark zum Overfitting. Daher wurde als zweites Modell der Random Forest Regressor gewählt. Dieser besteht aus mehreren unkorrelierten Entscheidungsbäumen. Dadurch wird das Overfitting von Entscheidungsbäumen vermieden und somit eine bessere Generalisierung ermöglicht.
Für das Modell wird der Random Forest Regressor von Scikit-Learn implementiert. Dieser bietet eine Reihe von Parametern welche in der Hyperparameteroptimierung angepasst werden können. Die optimalen Parameter werden ebenfalls mit dem Gridsearchalgorithmus ermittelt.
Um der Komplexität des Gridsearchalgorithmus entgegenzuwirken werden Parameter ausgewählt, welche ausführlich optimiert werden. Zuvor wurden durch Tests Parameter ermittelt, welche eine signifikante Änderung für das Training bedeuteten. Parameter, welche eine starke Korrelation aufweisen (zb. min_samples_split und min_samples_leaf) haben einen sehr ähnlichen Effekt auf das Training, weshalb lediglich einer dieser Parameter optimiert wird.
Aus diesen Gründen werden folgende Parameter in der Hyperparameteroptimierung angewandt:
Die anderen Parameter werden auf Default gesetzt oder auf Werte, die bei zuvor durchgeführten Tests am sinnvollsten erschienen.
def RandomForestRegressor_train(X, y, cross_validation=False, hyperparameter=None, n_splits=3, n_repeats=1, seed=42, test_for_professor = False):
"""Trainiert ein Random Forest Regressor Model mit gegebenen Hyperparametern.
Falls Cross Validation auf Wahr gesetzt wurde, werden RFR Modelle mit Hilfe einer
Datensatzaufteilung durch KFold trainiert um optimale Hyperparameter zu bestimmen.
Args:
X (np.array): Features des Trainingsdatensatzes
y (np.array): Labels des Trainingsdatensatz
cross_validation (bool): Ob Cross Validation verwendet werden soll um Hyperparameter zu bestimmen,
ansonsten wird ein Modell mit den übergebenen Hyperparametern trainiert. Defaults ist False
hyperparameter (dict oder None): Übergabe der Hyperparameter für das Modell bei cross_validation = True. Defaults ist None
n_splits (int): Anzahl an Spaltungen für Cross Validation. Defaults ist 3
n_repeats (n_repeats): Wiederholungen der Cross Validation. Defaults ist 1
seed (int): Seed für den KFold Algorithmus. Defaults ist 42
test_for_professor (bool): Test für den Professor/Kommilitonen um schneller zu trainieren. Defaults ist False
Returns:
cross_validation == True:
train_config (dict): Ein Array von Objekten, welcher die Hyperparameter und Metriken des Trainings beinhaltet
cross_validation == False:
model (object): Das trainierte Model
Raise:
ValueError: Falls beim Trainieren eines Modells in dem Hyperparameter Dictionary ein falscher Wert übergeben wurde.
"""
if cross_validation:
zeitanfang = time.time()
train_config = {
"n_estimators":[],
"max_depth":[],
"min_samples_split":[],
"min_weight_fraction_leaf":[],
"ccp_alpha":[],
"oob_score":[],
"max_features":[],
"r2score_train":[],
"mse_train":[],
"acc_train":[],
"r2score_val":[],
"mse_val":[],
"acc_val":[],
"time":[],
}
n_estimators=[1000]
max_depth= [i for i in range(1,30,1)]
min_samples_split=np.unique(np.round(np.logspace(1, 6, num=10, base=2)).astype(int))
min_weight_fraction_leaf=[0]#is not optimized for time reasons. However, zero is usually best.
oob_score=[True]#,False]
ccp_alpha=[0] #is not optimized for time reasons. However, zero is usually best.
max_features=['auto', 'sqrt','log2']
if test_for_professor:
#Test for fast run
n_estimators=[1000]
max_depth=[20,25]
min_samples_split=[2,4]
min_weight_fraction_leaf=[0]
oob_score=[False]
ccp_alpha=[0]
max_features=['auto', 'sqrt']
cvvr = CrossValidationValueRecorder()
rkf = RepeatedKFold(n_splits=n_splits, n_repeats=n_repeats, random_state=seed)
num_train = ProductLength([n_estimators, max_depth, min_samples_split, min_weight_fraction_leaf,oob_score, ccp_alpha, max_features])
print(f'Step/Maxsteps | Estimator | MaxDepth | MinSampleSplit | Minweightfractionleaf | oobscore | ccpalpha | max_features')
for i,(n_e,md,ms,mw,oob,ccp,mf) in enumerate(itertools.product(n_estimators, max_depth, min_samples_split, min_weight_fraction_leaf, oob_score, ccp_alpha,max_features)):
print(f'{i+1:5d}/{num_train} {n_e:5d} {md:2d} {ms:2d} {mw:.3f} {oob:.3f} {ccp:.3f} {mf}', end='')
train_config["n_estimators"].append(n_e)
train_config["max_depth"].append(md)
train_config["min_samples_split"].append(ms)
train_config["min_weight_fraction_leaf"].append(mw)
train_config["oob_score"].append(oob)
train_config["ccp_alpha"].append(ccp)
train_config["max_features"].append(mf)
cvvr.Reset()
trainingTimeBegin = time.time()
for train_index, val_index in rkf.split(X):
X_train, X_val = X[train_index], X[val_index]
y_train, y_val = y[train_index], y[val_index]
rfr=RandomForestRegressor(max_depth=md, min_samples_split=ms, min_weight_fraction_leaf=mw, oob_score=oob, ccp_alpha=ccp, random_state=seed, n_jobs=-1, n_estimators=n_e, max_features=mf)
model = rfr.fit(X_train, y_train)
#val
y_pred = model.predict(X_val)
cvvr.AddValidationMetric(y_val, y_pred)
#Train
y_pred = model.predict(X_train)
cvvr.AddTrainMetric(y_train, y_pred)
trainingTime = time.time()-trainingTimeBegin
train_config["time"].append(trainingTime)
print(' ->',cvvr.GetMSE())
# Add Scores to evaluate
cvvr.UpdateConfig(train_config)
processingTime = time.time()-zeitanfang
print(f"Time Taken {processingTime:.3f}s")
return train_config
else:
rfr=RandomForestRegressor(random_state=seed, n_jobs=-1, n_estimators=hyperparameter['n_estimators'],
max_depth=hyperparameter['max_depth'],min_samples_split=hyperparameter['min_samples_split'],
min_weight_fraction_leaf=hyperparameter['min_weight_fraction_leaf'],oob_score=hyperparameter['oob_score'],
ccp_alpha=hyperparameter['ccp_alpha'], max_features=hyperparameter['max_features'])
model = rfr.fit(X, y)
return model
Ausführung der Trainingsfunktionen der Modelle. Nach jedem Modelldurchlauf werden die Ergebnisse in eine .csv Datei zwischengespeichert.
train_df, test_df = get_datasets(logarithm=True, feature_selection=False)
X_train = train_df.drop("quality",axis=1).values
X_test = test_df.drop("quality",axis=1).values
y_train = train_df["quality"].values
y_test = test_df["quality"].values
train_config = RandomForestRegressor_train(X_train,y_train,cross_validation=True, test_for_professor = test_for_professor)
df = pd.DataFrame.from_dict(train_config)
df = df.sort_values(by=['mse_val'])
if not test_for_professor:
df.to_csv('results/train_conf_tree.csv',index=False)
Step/Maxsteps | Estimator | MaxDepth | MinSampleSplit | Minweightfractionleaf | oobscore | ccpalpha | max_features
1/870 1000 1 2 0.000 1.000 0.000 auto -> 0.6246662850329954
2/870 1000 1 2 0.000 1.000 0.000 sqrt -> 0.6494371022085937
3/870 1000 1 2 0.000 1.000 0.000 log2 -> 0.6494371022085937
4/870 1000 1 3 0.000 1.000 0.000 auto -> 0.6246662850329954
5/870 1000 1 3 0.000 1.000 0.000 sqrt -> 0.6494371022085937
6/870 1000 1 3 0.000 1.000 0.000 log2 -> 0.6494371022085937
7/870 1000 1 4 0.000 1.000 0.000 auto -> 0.6246662850329954
8/870 1000 1 4 0.000 1.000 0.000 sqrt -> 0.6494371022085937
9/870 1000 1 4 0.000 1.000 0.000 log2 -> 0.6494371022085937
10/870 1000 1 6 0.000 1.000 0.000 auto -> 0.6246662850329954
11/870 1000 1 6 0.000 1.000 0.000 sqrt -> 0.6494371022085937
12/870 1000 1 6 0.000 1.000 0.000 log2 -> 0.6494371022085936
13/870 1000 1 9 0.000 1.000 0.000 auto -> 0.6246662850329954
14/870 1000 1 9 0.000 1.000 0.000 sqrt -> 0.6494371022085937
15/870 1000 1 9 0.000 1.000 0.000 log2 -> 0.6494371022085937
16/870 1000 1 14 0.000 1.000 0.000 auto -> 0.6246662850329955
17/870 1000 1 14 0.000 1.000 0.000 sqrt -> 0.6494371022085937
18/870 1000 1 14 0.000 1.000 0.000 log2 -> 0.6494371022085937
19/870 1000 1 20 0.000 1.000 0.000 auto -> 0.6246662850329954
20/870 1000 1 20 0.000 1.000 0.000 sqrt -> 0.6494371022085937
21/870 1000 1 20 0.000 1.000 0.000 log2 -> 0.6494371022085935
22/870 1000 1 30 0.000 1.000 0.000 auto -> 0.6246662850329954
23/870 1000 1 30 0.000 1.000 0.000 sqrt -> 0.6494371022085937
24/870 1000 1 30 0.000 1.000 0.000 log2 -> 0.6494371022085937
25/870 1000 1 44 0.000 1.000 0.000 auto -> 0.6246662850329955
26/870 1000 1 44 0.000 1.000 0.000 sqrt -> 0.6494371022085937
27/870 1000 1 44 0.000 1.000 0.000 log2 -> 0.6494371022085935
28/870 1000 1 64 0.000 1.000 0.000 auto -> 0.6246662850329954
29/870 1000 1 64 0.000 1.000 0.000 sqrt -> 0.6494371022085935
30/870 1000 1 64 0.000 1.000 0.000 log2 -> 0.6494371022085935
31/870 1000 2 2 0.000 1.000 0.000 auto -> 0.5569543188751295
32/870 1000 2 2 0.000 1.000 0.000 sqrt -> 0.5935648257281153
33/870 1000 2 2 0.000 1.000 0.000 log2 -> 0.5935648257281153
34/870 1000 2 3 0.000 1.000 0.000 auto -> 0.5569543188751295
35/870 1000 2 3 0.000 1.000 0.000 sqrt -> 0.5935648257281153
36/870 1000 2 3 0.000 1.000 0.000 log2 -> 0.5935648257281153
37/870 1000 2 4 0.000 1.000 0.000 auto -> 0.5569543188751295
38/870 1000 2 4 0.000 1.000 0.000 sqrt -> 0.5935648257281153
39/870 1000 2 4 0.000 1.000 0.000 log2 -> 0.5935648257281153
40/870 1000 2 6 0.000 1.000 0.000 auto -> 0.5569543188751295
41/870 1000 2 6 0.000 1.000 0.000 sqrt -> 0.5935648257281153
42/870 1000 2 6 0.000 1.000 0.000 log2 -> 0.5935648257281153
43/870 1000 2 9 0.000 1.000 0.000 auto -> 0.5569543188751295
44/870 1000 2 9 0.000 1.000 0.000 sqrt -> 0.5935648257281153
45/870 1000 2 9 0.000 1.000 0.000 log2 -> 0.5935648257281153
46/870 1000 2 14 0.000 1.000 0.000 auto -> 0.5569543188751295
47/870 1000 2 14 0.000 1.000 0.000 sqrt -> 0.5935648257281153
48/870 1000 2 14 0.000 1.000 0.000 log2 -> 0.5935648257281154
49/870 1000 2 20 0.000 1.000 0.000 auto -> 0.5569543188751295
50/870 1000 2 20 0.000 1.000 0.000 sqrt -> 0.5935648257281153
51/870 1000 2 20 0.000 1.000 0.000 log2 -> 0.5935648257281153
52/870 1000 2 30 0.000 1.000 0.000 auto -> 0.5569543188751295
53/870 1000 2 30 0.000 1.000 0.000 sqrt -> 0.5935590171994316
54/870 1000 2 30 0.000 1.000 0.000 log2 -> 0.5935590171994317
55/870 1000 2 44 0.000 1.000 0.000 auto -> 0.5569543188751295
56/870 1000 2 44 0.000 1.000 0.000 sqrt -> 0.5936038077268836
57/870 1000 2 44 0.000 1.000 0.000 log2 -> 0.5936038077268836
58/870 1000 2 64 0.000 1.000 0.000 auto -> 0.5569543188751295
59/870 1000 2 64 0.000 1.000 0.000 sqrt -> 0.5936742028265631
60/870 1000 2 64 0.000 1.000 0.000 log2 -> 0.5936742028265631
61/870 1000 3 2 0.000 1.000 0.000 auto -> 0.5298336477485531
62/870 1000 3 2 0.000 1.000 0.000 sqrt -> 0.5552120953049079
63/870 1000 3 2 0.000 1.000 0.000 log2 -> 0.5552120953049079
64/870 1000 3 3 0.000 1.000 0.000 auto -> 0.5298336477485531
65/870 1000 3 3 0.000 1.000 0.000 sqrt -> 0.5552249795056975
66/870 1000 3 3 0.000 1.000 0.000 log2 -> 0.5552249795056975
67/870 1000 3 4 0.000 1.000 0.000 auto -> 0.5298336477485532
68/870 1000 3 4 0.000 1.000 0.000 sqrt -> 0.5552074660107625
69/870 1000 3 4 0.000 1.000 0.000 log2 -> 0.5552074660107623
70/870 1000 3 6 0.000 1.000 0.000 auto -> 0.529834059654752
71/870 1000 3 6 0.000 1.000 0.000 sqrt -> 0.5551277008090799
72/870 1000 3 6 0.000 1.000 0.000 log2 -> 0.5551277008090799
73/870 1000 3 9 0.000 1.000 0.000 auto -> 0.5298313073854425
74/870 1000 3 9 0.000 1.000 0.000 sqrt -> 0.5552345557030609
75/870 1000 3 9 0.000 1.000 0.000 log2 -> 0.5552345557030608
76/870 1000 3 14 0.000 1.000 0.000 auto -> 0.5298231498220131
77/870 1000 3 14 0.000 1.000 0.000 sqrt -> 0.555318292304875
78/870 1000 3 14 0.000 1.000 0.000 log2 -> 0.5553182923048751
79/870 1000 3 20 0.000 1.000 0.000 auto -> 0.529810954144054
80/870 1000 3 20 0.000 1.000 0.000 sqrt -> 0.5553943804176994
81/870 1000 3 20 0.000 1.000 0.000 log2 -> 0.5553943804176994
82/870 1000 3 30 0.000 1.000 0.000 auto -> 0.5298306660128583
83/870 1000 3 30 0.000 1.000 0.000 sqrt -> 0.5554713333857669
84/870 1000 3 30 0.000 1.000 0.000 log2 -> 0.5554713333857669
85/870 1000 3 44 0.000 1.000 0.000 auto -> 0.5299803765691715
86/870 1000 3 44 0.000 1.000 0.000 sqrt -> 0.5556215296398119
87/870 1000 3 44 0.000 1.000 0.000 log2 -> 0.5556215296398119
88/870 1000 3 64 0.000 1.000 0.000 auto -> 0.5301692839506301
89/870 1000 3 64 0.000 1.000 0.000 sqrt -> 0.5559851151436761
90/870 1000 3 64 0.000 1.000 0.000 log2 -> 0.5559851151436761
91/870 1000 4 2 0.000 1.000 0.000 auto -> 0.5044670229959504
92/870 1000 4 2 0.000 1.000 0.000 sqrt -> 0.5254048474104165
93/870 1000 4 2 0.000 1.000 0.000 log2 -> 0.5254048474104164
94/870 1000 4 3 0.000 1.000 0.000 auto -> 0.5044832121258706
95/870 1000 4 3 0.000 1.000 0.000 sqrt -> 0.5255049656512056
96/870 1000 4 3 0.000 1.000 0.000 log2 -> 0.5255049656512057
97/870 1000 4 4 0.000 1.000 0.000 auto -> 0.5044902245225096
98/870 1000 4 4 0.000 1.000 0.000 sqrt -> 0.5257212462164901
99/870 1000 4 4 0.000 1.000 0.000 log2 -> 0.5257212462164901
100/870 1000 4 6 0.000 1.000 0.000 auto -> 0.504541998916422
101/870 1000 4 6 0.000 1.000 0.000 sqrt -> 0.5253781353601535
102/870 1000 4 6 0.000 1.000 0.000 log2 -> 0.5253781353601535
103/870 1000 4 9 0.000 1.000 0.000 auto -> 0.504502808896098
104/870 1000 4 9 0.000 1.000 0.000 sqrt -> 0.5253807898939685
105/870 1000 4 9 0.000 1.000 0.000 log2 -> 0.5253807898939685
106/870 1000 4 14 0.000 1.000 0.000 auto -> 0.5045153096268097
107/870 1000 4 14 0.000 1.000 0.000 sqrt -> 0.5255414638331574
108/870 1000 4 14 0.000 1.000 0.000 log2 -> 0.5255414638331574
109/870 1000 4 20 0.000 1.000 0.000 auto -> 0.504627200510556
110/870 1000 4 20 0.000 1.000 0.000 sqrt -> 0.5258943898823267
111/870 1000 4 20 0.000 1.000 0.000 log2 -> 0.5258943898823267
112/870 1000 4 30 0.000 1.000 0.000 auto -> 0.5050124082578821
113/870 1000 4 30 0.000 1.000 0.000 sqrt -> 0.5265696550658036
114/870 1000 4 30 0.000 1.000 0.000 log2 -> 0.5265696550658036
115/870 1000 4 44 0.000 1.000 0.000 auto -> 0.5059005664501636
116/870 1000 4 44 0.000 1.000 0.000 sqrt -> 0.5271378517654594
117/870 1000 4 44 0.000 1.000 0.000 log2 -> 0.5271378517654594
118/870 1000 4 64 0.000 1.000 0.000 auto -> 0.5073593862001251
119/870 1000 4 64 0.000 1.000 0.000 sqrt -> 0.5281195279313046
120/870 1000 4 64 0.000 1.000 0.000 log2 -> 0.5281195279313046
121/870 1000 5 2 0.000 1.000 0.000 auto -> 0.4834508473372005
122/870 1000 5 2 0.000 1.000 0.000 sqrt -> 0.5021246824031157
123/870 1000 5 2 0.000 1.000 0.000 log2 -> 0.5021246824031159
124/870 1000 5 3 0.000 1.000 0.000 auto -> 0.4834628057753763
125/870 1000 5 3 0.000 1.000 0.000 sqrt -> 0.502128030061811
126/870 1000 5 3 0.000 1.000 0.000 log2 -> 0.502128030061811
127/870 1000 5 4 0.000 1.000 0.000 auto -> 0.4835214827548278
128/870 1000 5 4 0.000 1.000 0.000 sqrt -> 0.502209598038378
129/870 1000 5 4 0.000 1.000 0.000 log2 -> 0.502209598038378
130/870 1000 5 6 0.000 1.000 0.000 auto -> 0.48358503956146787
131/870 1000 5 6 0.000 1.000 0.000 sqrt -> 0.5019889599148238
132/870 1000 5 6 0.000 1.000 0.000 log2 -> 0.5019889599148236
133/870 1000 5 9 0.000 1.000 0.000 auto -> 0.483654924694856
134/870 1000 5 9 0.000 1.000 0.000 sqrt -> 0.5019237783745473
135/870 1000 5 9 0.000 1.000 0.000 log2 -> 0.5019237783745473
136/870 1000 5 14 0.000 1.000 0.000 auto -> 0.4839057051385467
137/870 1000 5 14 0.000 1.000 0.000 sqrt -> 0.5025306851475689
138/870 1000 5 14 0.000 1.000 0.000 log2 -> 0.5025306851475689
139/870 1000 5 20 0.000 1.000 0.000 auto -> 0.48441149397869543
140/870 1000 5 20 0.000 1.000 0.000 sqrt -> 0.5033117001036186
141/870 1000 5 20 0.000 1.000 0.000 log2 -> 0.5033117001036186
142/870 1000 5 30 0.000 1.000 0.000 auto -> 0.485740999887274
143/870 1000 5 30 0.000 1.000 0.000 sqrt -> 0.5043063698906326
144/870 1000 5 30 0.000 1.000 0.000 log2 -> 0.5043063698906326
145/870 1000 5 44 0.000 1.000 0.000 auto -> 0.48786820132612974
146/870 1000 5 44 0.000 1.000 0.000 sqrt -> 0.5059573838096176
147/870 1000 5 44 0.000 1.000 0.000 log2 -> 0.5059573838096176
148/870 1000 5 64 0.000 1.000 0.000 auto -> 0.49139999867464645
149/870 1000 5 64 0.000 1.000 0.000 sqrt -> 0.5083795960342711
150/870 1000 5 64 0.000 1.000 0.000 log2 -> 0.508379596034271
151/870 1000 6 2 0.000 1.000 0.000 auto -> 0.4663477884909431
152/870 1000 6 2 0.000 1.000 0.000 sqrt -> 0.4807797524535348
153/870 1000 6 2 0.000 1.000 0.000 log2 -> 0.4807797524535349
154/870 1000 6 3 0.000 1.000 0.000 auto -> 0.46641186778486504
155/870 1000 6 3 0.000 1.000 0.000 sqrt -> 0.4807449353078023
156/870 1000 6 3 0.000 1.000 0.000 log2 -> 0.4807449353078023
157/870 1000 6 4 0.000 1.000 0.000 auto -> 0.4664371365554727
158/870 1000 6 4 0.000 1.000 0.000 sqrt -> 0.48118057193966557
159/870 1000 6 4 0.000 1.000 0.000 log2 -> 0.4811805719396656
160/870 1000 6 6 0.000 1.000 0.000 auto -> 0.46664977000715974
161/870 1000 6 6 0.000 1.000 0.000 sqrt -> 0.48113049866211716
162/870 1000 6 6 0.000 1.000 0.000 log2 -> 0.48113049866211716
163/870 1000 6 9 0.000 1.000 0.000 auto -> 0.4669263879254098
164/870 1000 6 9 0.000 1.000 0.000 sqrt -> 0.4814768966484728
165/870 1000 6 9 0.000 1.000 0.000 log2 -> 0.4814768966484728
166/870 1000 6 14 0.000 1.000 0.000 auto -> 0.4678325949548899
167/870 1000 6 14 0.000 1.000 0.000 sqrt -> 0.4821969638181569
168/870 1000 6 14 0.000 1.000 0.000 log2 -> 0.4821969638181569
169/870 1000 6 20 0.000 1.000 0.000 auto -> 0.4690013801034227
170/870 1000 6 20 0.000 1.000 0.000 sqrt -> 0.48457314344077623
171/870 1000 6 20 0.000 1.000 0.000 log2 -> 0.48457314344077623
172/870 1000 6 30 0.000 1.000 0.000 auto -> 0.4715524051815676
173/870 1000 6 30 0.000 1.000 0.000 sqrt -> 0.48685249056950797
174/870 1000 6 30 0.000 1.000 0.000 log2 -> 0.48685249056950797
175/870 1000 6 44 0.000 1.000 0.000 auto -> 0.4750632927646721
176/870 1000 6 44 0.000 1.000 0.000 sqrt -> 0.48982648723748684
177/870 1000 6 44 0.000 1.000 0.000 log2 -> 0.48982648723748684
178/870 1000 6 64 0.000 1.000 0.000 auto -> 0.4804679990281362
179/870 1000 6 64 0.000 1.000 0.000 sqrt -> 0.49428565157353116
180/870 1000 6 64 0.000 1.000 0.000 log2 -> 0.49428565157353116
181/870 1000 7 2 0.000 1.000 0.000 auto -> 0.4514614100649796
182/870 1000 7 2 0.000 1.000 0.000 sqrt -> 0.4622448346267553
183/870 1000 7 2 0.000 1.000 0.000 log2 -> 0.4622448346267553
184/870 1000 7 3 0.000 1.000 0.000 auto -> 0.4513462508044291
185/870 1000 7 3 0.000 1.000 0.000 sqrt -> 0.46241027247506045
186/870 1000 7 3 0.000 1.000 0.000 log2 -> 0.46241027247506045
187/870 1000 7 4 0.000 1.000 0.000 auto -> 0.45169722772176507
188/870 1000 7 4 0.000 1.000 0.000 sqrt -> 0.4629825658720172
189/870 1000 7 4 0.000 1.000 0.000 log2 -> 0.4629825658720172
190/870 1000 7 6 0.000 1.000 0.000 auto -> 0.451922075692098
191/870 1000 7 6 0.000 1.000 0.000 sqrt -> 0.4638180638617353
192/870 1000 7 6 0.000 1.000 0.000 log2 -> 0.4638180638617353
193/870 1000 7 9 0.000 1.000 0.000 auto -> 0.4527566769847464
194/870 1000 7 9 0.000 1.000 0.000 sqrt -> 0.464515933962007
195/870 1000 7 9 0.000 1.000 0.000 log2 -> 0.464515933962007
196/870 1000 7 14 0.000 1.000 0.000 auto -> 0.4545514782773476
197/870 1000 7 14 0.000 1.000 0.000 sqrt -> 0.466341249278812
198/870 1000 7 14 0.000 1.000 0.000 log2 -> 0.466341249278812
199/870 1000 7 20 0.000 1.000 0.000 auto -> 0.45689847778679743
200/870 1000 7 20 0.000 1.000 0.000 sqrt -> 0.4688587090723996
201/870 1000 7 20 0.000 1.000 0.000 log2 -> 0.4688587090723996
202/870 1000 7 30 0.000 1.000 0.000 auto -> 0.46075576651889966
203/870 1000 7 30 0.000 1.000 0.000 sqrt -> 0.4726876039553877
204/870 1000 7 30 0.000 1.000 0.000 log2 -> 0.4726876039553876
205/870 1000 7 44 0.000 1.000 0.000 auto -> 0.4659652839466588
206/870 1000 7 44 0.000 1.000 0.000 sqrt -> 0.4782185727345909
207/870 1000 7 44 0.000 1.000 0.000 log2 -> 0.4782185727345909
208/870 1000 7 64 0.000 1.000 0.000 auto -> 0.4731371635743515
209/870 1000 7 64 0.000 1.000 0.000 sqrt -> 0.48357382795534193
210/870 1000 7 64 0.000 1.000 0.000 log2 -> 0.48357382795534193
211/870 1000 8 2 0.000 1.000 0.000 auto -> 0.4375334090374429
212/870 1000 8 2 0.000 1.000 0.000 sqrt -> 0.4471558697577829
213/870 1000 8 2 0.000 1.000 0.000 log2 -> 0.4471558697577829
214/870 1000 8 3 0.000 1.000 0.000 auto -> 0.4374494404687152
215/870 1000 8 3 0.000 1.000 0.000 sqrt -> 0.44679165924633013
216/870 1000 8 3 0.000 1.000 0.000 log2 -> 0.4467916592463302
217/870 1000 8 4 0.000 1.000 0.000 auto -> 0.4375909807341605
218/870 1000 8 4 0.000 1.000 0.000 sqrt -> 0.4475288457919054
219/870 1000 8 4 0.000 1.000 0.000 log2 -> 0.4475288457919054
220/870 1000 8 6 0.000 1.000 0.000 auto -> 0.43861061059188233
221/870 1000 8 6 0.000 1.000 0.000 sqrt -> 0.44831571443783796
222/870 1000 8 6 0.000 1.000 0.000 log2 -> 0.44831571443783796
223/870 1000 8 9 0.000 1.000 0.000 auto -> 0.44020047474293406
224/870 1000 8 9 0.000 1.000 0.000 sqrt -> 0.4509913844134506
225/870 1000 8 9 0.000 1.000 0.000 log2 -> 0.4509913844134506
226/870 1000 8 14 0.000 1.000 0.000 auto -> 0.44316298326806686
227/870 1000 8 14 0.000 1.000 0.000 sqrt -> 0.453395793578989
228/870 1000 8 14 0.000 1.000 0.000 log2 -> 0.453395793578989
229/870 1000 8 20 0.000 1.000 0.000 auto -> 0.4466454769755462
230/870 1000 8 20 0.000 1.000 0.000 sqrt -> 0.45743504340536933
231/870 1000 8 20 0.000 1.000 0.000 log2 -> 0.45743504340536933
232/870 1000 8 30 0.000 1.000 0.000 auto -> 0.4522662170615552
233/870 1000 8 30 0.000 1.000 0.000 sqrt -> 0.46261396821429107
234/870 1000 8 30 0.000 1.000 0.000 log2 -> 0.4626139682142911
235/870 1000 8 44 0.000 1.000 0.000 auto -> 0.4592241308414393
236/870 1000 8 44 0.000 1.000 0.000 sqrt -> 0.4695068447854564
237/870 1000 8 44 0.000 1.000 0.000 log2 -> 0.4695068447854564
238/870 1000 8 64 0.000 1.000 0.000 auto -> 0.46818581912238305
239/870 1000 8 64 0.000 1.000 0.000 sqrt -> 0.47722857093086163
240/870 1000 8 64 0.000 1.000 0.000 log2 -> 0.47722857093086163
241/870 1000 9 2 0.000 1.000 0.000 auto -> 0.4255286131620706
242/870 1000 9 2 0.000 1.000 0.000 sqrt -> 0.43345760786671245
243/870 1000 9 2 0.000 1.000 0.000 log2 -> 0.43345760786671245
244/870 1000 9 3 0.000 1.000 0.000 auto -> 0.4256822301271836
245/870 1000 9 3 0.000 1.000 0.000 sqrt -> 0.43333076557971434
246/870 1000 9 3 0.000 1.000 0.000 log2 -> 0.43333076557971434
247/870 1000 9 4 0.000 1.000 0.000 auto -> 0.42625047676479905
248/870 1000 9 4 0.000 1.000 0.000 sqrt -> 0.433905974329624
249/870 1000 9 4 0.000 1.000 0.000 log2 -> 0.433905974329624
250/870 1000 9 6 0.000 1.000 0.000 auto -> 0.42750416867369595
251/870 1000 9 6 0.000 1.000 0.000 sqrt -> 0.4354554581999885
252/870 1000 9 6 0.000 1.000 0.000 log2 -> 0.4354554581999885
253/870 1000 9 9 0.000 1.000 0.000 auto -> 0.4298137420848127
254/870 1000 9 9 0.000 1.000 0.000 sqrt -> 0.4386033999955601
255/870 1000 9 9 0.000 1.000 0.000 log2 -> 0.4386033999955601
256/870 1000 9 14 0.000 1.000 0.000 auto -> 0.43382926507715197
257/870 1000 9 14 0.000 1.000 0.000 sqrt -> 0.44368448350673884
258/870 1000 9 14 0.000 1.000 0.000 log2 -> 0.44368448350673884
259/870 1000 9 20 0.000 1.000 0.000 auto -> 0.4386083148207323
260/870 1000 9 20 0.000 1.000 0.000 sqrt -> 0.4475513700040299
261/870 1000 9 20 0.000 1.000 0.000 log2 -> 0.4475513700040299
262/870 1000 9 30 0.000 1.000 0.000 auto -> 0.44582708099186225
263/870 1000 9 30 0.000 1.000 0.000 sqrt -> 0.45557656029098076
264/870 1000 9 30 0.000 1.000 0.000 log2 -> 0.45557656029098076
265/870 1000 9 44 0.000 1.000 0.000 auto -> 0.4545208777574154
266/870 1000 9 44 0.000 1.000 0.000 sqrt -> 0.46305106950293956
267/870 1000 9 44 0.000 1.000 0.000 log2 -> 0.46305106950293956
268/870 1000 9 64 0.000 1.000 0.000 auto -> 0.4650474974042275
269/870 1000 9 64 0.000 1.000 0.000 sqrt -> 0.4723671410907988
270/870 1000 9 64 0.000 1.000 0.000 log2 -> 0.4723671410907988
271/870 1000 10 2 0.000 1.000 0.000 auto -> 0.4152388217490967
272/870 1000 10 2 0.000 1.000 0.000 sqrt -> 0.4208949461234523
273/870 1000 10 2 0.000 1.000 0.000 log2 -> 0.4208949461234523
274/870 1000 10 3 0.000 1.000 0.000 auto -> 0.4156685318376591
275/870 1000 10 3 0.000 1.000 0.000 sqrt -> 0.4207729838769152
276/870 1000 10 3 0.000 1.000 0.000 log2 -> 0.4207729838769152
277/870 1000 10 4 0.000 1.000 0.000 auto -> 0.4164991792623752
278/870 1000 10 4 0.000 1.000 0.000 sqrt -> 0.42239303882986295
279/870 1000 10 4 0.000 1.000 0.000 log2 -> 0.42239303882986295
280/870 1000 10 6 0.000 1.000 0.000 auto -> 0.4181915802710163
281/870 1000 10 6 0.000 1.000 0.000 sqrt -> 0.425022026625395
282/870 1000 10 6 0.000 1.000 0.000 log2 -> 0.42502202662539496
283/870 1000 10 9 0.000 1.000 0.000 auto -> 0.42115726254819497
284/870 1000 10 9 0.000 1.000 0.000 sqrt -> 0.42862261585425093
285/870 1000 10 9 0.000 1.000 0.000 log2 -> 0.42862261585425093
286/870 1000 10 14 0.000 1.000 0.000 auto -> 0.4267243235548084
287/870 1000 10 14 0.000 1.000 0.000 sqrt -> 0.434812637481164
288/870 1000 10 14 0.000 1.000 0.000 log2 -> 0.434812637481164
289/870 1000 10 20 0.000 1.000 0.000 auto -> 0.4327560477926891
290/870 1000 10 20 0.000 1.000 0.000 sqrt -> 0.44134207244325907
291/870 1000 10 20 0.000 1.000 0.000 log2 -> 0.44134207244325907
292/870 1000 10 30 0.000 1.000 0.000 auto -> 0.44165912171696625
293/870 1000 10 30 0.000 1.000 0.000 sqrt -> 0.45027598751165293
294/870 1000 10 30 0.000 1.000 0.000 log2 -> 0.45027598751165304
295/870 1000 10 44 0.000 1.000 0.000 auto -> 0.45150231905946253
296/870 1000 10 44 0.000 1.000 0.000 sqrt -> 0.45916744764728334
297/870 1000 10 44 0.000 1.000 0.000 log2 -> 0.45916744764728334
298/870 1000 10 64 0.000 1.000 0.000 auto -> 0.46313186731669015
299/870 1000 10 64 0.000 1.000 0.000 sqrt -> 0.47027118680306307
300/870 1000 10 64 0.000 1.000 0.000 log2 -> 0.47027118680306307
301/870 1000 11 2 0.000 1.000 0.000 auto -> 0.40768020257822196
302/870 1000 11 2 0.000 1.000 0.000 sqrt -> 0.4106548739405648
303/870 1000 11 2 0.000 1.000 0.000 log2 -> 0.4106548739405649
304/870 1000 11 3 0.000 1.000 0.000 auto -> 0.4084256112946667
305/870 1000 11 3 0.000 1.000 0.000 sqrt -> 0.4119550945078718
306/870 1000 11 3 0.000 1.000 0.000 log2 -> 0.4119550945078718
307/870 1000 11 4 0.000 1.000 0.000 auto -> 0.40945441529348625
308/870 1000 11 4 0.000 1.000 0.000 sqrt -> 0.4133022571455623
309/870 1000 11 4 0.000 1.000 0.000 log2 -> 0.4133022571455624
310/870 1000 11 6 0.000 1.000 0.000 auto -> 0.411409730537073
311/870 1000 11 6 0.000 1.000 0.000 sqrt -> 0.4155556660225277
312/870 1000 11 6 0.000 1.000 0.000 log2 -> 0.4155556660225277
313/870 1000 11 9 0.000 1.000 0.000 auto -> 0.415193104507998
314/870 1000 11 9 0.000 1.000 0.000 sqrt -> 0.42145180796202975
315/870 1000 11 9 0.000 1.000 0.000 log2 -> 0.4214518079620297
316/870 1000 11 14 0.000 1.000 0.000 auto -> 0.4216689489393315
317/870 1000 11 14 0.000 1.000 0.000 sqrt -> 0.428104014918679
318/870 1000 11 14 0.000 1.000 0.000 log2 -> 0.428104014918679
319/870 1000 11 20 0.000 1.000 0.000 auto -> 0.42862641317797245
320/870 1000 11 20 0.000 1.000 0.000 sqrt -> 0.4360311375773171
321/870 1000 11 20 0.000 1.000 0.000 log2 -> 0.436031137577317
322/870 1000 11 30 0.000 1.000 0.000 auto -> 0.43856668238874724
323/870 1000 11 30 0.000 1.000 0.000 sqrt -> 0.44671918598872024
324/870 1000 11 30 0.000 1.000 0.000 log2 -> 0.44671918598872024
325/870 1000 11 44 0.000 1.000 0.000 auto -> 0.4496209790028433
326/870 1000 11 44 0.000 1.000 0.000 sqrt -> 0.45641500541392505
327/870 1000 11 44 0.000 1.000 0.000 log2 -> 0.45641500541392505
328/870 1000 11 64 0.000 1.000 0.000 auto -> 0.4621214619549164
329/870 1000 11 64 0.000 1.000 0.000 sqrt -> 0.46868880185562506
330/870 1000 11 64 0.000 1.000 0.000 log2 -> 0.46868880185562506
331/870 1000 12 2 0.000 1.000 0.000 auto -> 0.40183432803502467
332/870 1000 12 2 0.000 1.000 0.000 sqrt -> 0.40355777894483597
333/870 1000 12 2 0.000 1.000 0.000 log2 -> 0.4035577789448361
334/870 1000 12 3 0.000 1.000 0.000 auto -> 0.4025332067471992
335/870 1000 12 3 0.000 1.000 0.000 sqrt -> 0.4040209346651015
336/870 1000 12 3 0.000 1.000 0.000 log2 -> 0.4040209346651016
337/870 1000 12 4 0.000 1.000 0.000 auto -> 0.4038629674884308
338/870 1000 12 4 0.000 1.000 0.000 sqrt -> 0.40630600690167656
339/870 1000 12 4 0.000 1.000 0.000 log2 -> 0.40630600690167656
340/870 1000 12 6 0.000 1.000 0.000 auto -> 0.4060374810768024
341/870 1000 12 6 0.000 1.000 0.000 sqrt -> 0.4093652424196255
342/870 1000 12 6 0.000 1.000 0.000 log2 -> 0.4093652424196255
343/870 1000 12 9 0.000 1.000 0.000 auto -> 0.410508381680101
344/870 1000 12 9 0.000 1.000 0.000 sqrt -> 0.4158764865887042
345/870 1000 12 9 0.000 1.000 0.000 log2 -> 0.4158764865887042
346/870 1000 12 14 0.000 1.000 0.000 auto -> 0.417823700514009
347/870 1000 12 14 0.000 1.000 0.000 sqrt -> 0.42322365781503873
348/870 1000 12 14 0.000 1.000 0.000 log2 -> 0.42322365781503873
349/870 1000 12 20 0.000 1.000 0.000 auto -> 0.425503495639727
350/870 1000 12 20 0.000 1.000 0.000 sqrt -> 0.43248987366264185
351/870 1000 12 20 0.000 1.000 0.000 log2 -> 0.43248987366264185
352/870 1000 12 30 0.000 1.000 0.000 auto -> 0.4364601428129078
353/870 1000 12 30 0.000 1.000 0.000 sqrt -> 0.44467455406788337
354/870 1000 12 30 0.000 1.000 0.000 log2 -> 0.44467455406788337
355/870 1000 12 44 0.000 1.000 0.000 auto -> 0.44841188592917286
356/870 1000 12 44 0.000 1.000 0.000 sqrt -> 0.4546229125182011
357/870 1000 12 44 0.000 1.000 0.000 log2 -> 0.4546229125182011
358/870 1000 12 64 0.000 1.000 0.000 auto -> 0.46138085040583476
359/870 1000 12 64 0.000 1.000 0.000 sqrt -> 0.4677584092078539
360/870 1000 12 64 0.000 1.000 0.000 log2 -> 0.4677584092078539
361/870 1000 13 2 0.000 1.000 0.000 auto -> 0.39820123993566686
362/870 1000 13 2 0.000 1.000 0.000 sqrt -> 0.3979353578374025
363/870 1000 13 2 0.000 1.000 0.000 log2 -> 0.3979353578374025
364/870 1000 13 3 0.000 1.000 0.000 auto -> 0.3985546195078061
365/870 1000 13 3 0.000 1.000 0.000 sqrt -> 0.39884652583246805
366/870 1000 13 3 0.000 1.000 0.000 log2 -> 0.39884652583246805
367/870 1000 13 4 0.000 1.000 0.000 auto -> 0.40001014403757046
368/870 1000 13 4 0.000 1.000 0.000 sqrt -> 0.4011246840500966
369/870 1000 13 4 0.000 1.000 0.000 log2 -> 0.40112468405009666
370/870 1000 13 6 0.000 1.000 0.000 auto -> 0.40262496923566166
371/870 1000 13 6 0.000 1.000 0.000 sqrt -> 0.4048290398049624
372/870 1000 13 6 0.000 1.000 0.000 log2 -> 0.4048290398049624
373/870 1000 13 9 0.000 1.000 0.000 auto -> 0.40753204698362827
374/870 1000 13 9 0.000 1.000 0.000 sqrt -> 0.4117213000283275
375/870 1000 13 9 0.000 1.000 0.000 log2 -> 0.4117213000283275
376/870 1000 13 14 0.000 1.000 0.000 auto -> 0.41525437614398936
377/870 1000 13 14 0.000 1.000 0.000 sqrt -> 0.4207095111795825
378/870 1000 13 14 0.000 1.000 0.000 log2 -> 0.4207095111795825
379/870 1000 13 20 0.000 1.000 0.000 auto -> 0.42343870829854735
380/870 1000 13 20 0.000 1.000 0.000 sqrt -> 0.42959746719155883
381/870 1000 13 20 0.000 1.000 0.000 log2 -> 0.4295974671915588
382/870 1000 13 30 0.000 1.000 0.000 auto -> 0.4350145126602707
383/870 1000 13 30 0.000 1.000 0.000 sqrt -> 0.44236743433597764
384/870 1000 13 30 0.000 1.000 0.000 log2 -> 0.44236743433597764
385/870 1000 13 44 0.000 1.000 0.000 auto -> 0.44748386968456494
386/870 1000 13 44 0.000 1.000 0.000 sqrt -> 0.4538156908219287
387/870 1000 13 44 0.000 1.000 0.000 log2 -> 0.4538156908219287
388/870 1000 13 64 0.000 1.000 0.000 auto -> 0.46101220110053304
389/870 1000 13 64 0.000 1.000 0.000 sqrt -> 0.46751706582183755
390/870 1000 13 64 0.000 1.000 0.000 log2 -> 0.46751706582183766
391/870 1000 14 2 0.000 1.000 0.000 auto -> 0.39510369064794126
392/870 1000 14 2 0.000 1.000 0.000 sqrt -> 0.3934743291521137
393/870 1000 14 2 0.000 1.000 0.000 log2 -> 0.3934743291521137
394/870 1000 14 3 0.000 1.000 0.000 auto -> 0.3957481276557419
395/870 1000 14 3 0.000 1.000 0.000 sqrt -> 0.3959088912690704
396/870 1000 14 3 0.000 1.000 0.000 log2 -> 0.3959088912690703
397/870 1000 14 4 0.000 1.000 0.000 auto -> 0.39690391313367696
398/870 1000 14 4 0.000 1.000 0.000 sqrt -> 0.3983541618710362
399/870 1000 14 4 0.000 1.000 0.000 log2 -> 0.39835416187103617
400/870 1000 14 6 0.000 1.000 0.000 auto -> 0.400243080206056
401/870 1000 14 6 0.000 1.000 0.000 sqrt -> 0.40165008149300746
402/870 1000 14 6 0.000 1.000 0.000 log2 -> 0.40165008149300735
403/870 1000 14 9 0.000 1.000 0.000 auto -> 0.40493900725328286
404/870 1000 14 9 0.000 1.000 0.000 sqrt -> 0.40864322630676697
405/870 1000 14 9 0.000 1.000 0.000 log2 -> 0.40864322630676697
406/870 1000 14 14 0.000 1.000 0.000 auto -> 0.41346433696667484
407/870 1000 14 14 0.000 1.000 0.000 sqrt -> 0.4173236980865858
408/870 1000 14 14 0.000 1.000 0.000 log2 -> 0.41732369808658576
409/870 1000 14 20 0.000 1.000 0.000 auto -> 0.42194265587858837
410/870 1000 14 20 0.000 1.000 0.000 sqrt -> 0.42832998629659996
411/870 1000 14 20 0.000 1.000 0.000 log2 -> 0.42832998629659996
412/870 1000 14 30 0.000 1.000 0.000 auto -> 0.43402937957781296
413/870 1000 14 30 0.000 1.000 0.000 sqrt -> 0.44093120367629074
414/870 1000 14 30 0.000 1.000 0.000 log2 -> 0.4409312036762907
415/870 1000 14 44 0.000 1.000 0.000 auto -> 0.4469732941834847
416/870 1000 14 44 0.000 1.000 0.000 sqrt -> 0.4532641851789842
417/870 1000 14 44 0.000 1.000 0.000 log2 -> 0.4532641851789842
418/870 1000 14 64 0.000 1.000 0.000 auto -> 0.4608130567450724
419/870 1000 14 64 0.000 1.000 0.000 sqrt -> 0.46722363184347665
420/870 1000 14 64 0.000 1.000 0.000 log2 -> 0.46722363184347665
421/870 1000 15 2 0.000 1.000 0.000 auto -> 0.3930964527321457
422/870 1000 15 2 0.000 1.000 0.000 sqrt -> 0.3919298848453381
423/870 1000 15 2 0.000 1.000 0.000 log2 -> 0.3919298848453381
424/870 1000 15 3 0.000 1.000 0.000 auto -> 0.3937134018196898
425/870 1000 15 3 0.000 1.000 0.000 sqrt -> 0.39260443656593974
426/870 1000 15 3 0.000 1.000 0.000 log2 -> 0.39260443656593974
427/870 1000 15 4 0.000 1.000 0.000 auto -> 0.39521050660886275
428/870 1000 15 4 0.000 1.000 0.000 sqrt -> 0.3945065725849528
429/870 1000 15 4 0.000 1.000 0.000 log2 -> 0.39450657258495286
430/870 1000 15 6 0.000 1.000 0.000 auto -> 0.39838055608690964
431/870 1000 15 6 0.000 1.000 0.000 sqrt -> 0.398820734103049
432/870 1000 15 6 0.000 1.000 0.000 log2 -> 0.39882073410304897
433/870 1000 15 9 0.000 1.000 0.000 auto -> 0.40355359567797305
434/870 1000 15 9 0.000 1.000 0.000 sqrt -> 0.4064003919711488
435/870 1000 15 9 0.000 1.000 0.000 log2 -> 0.4064003919711488
436/870 1000 15 14 0.000 1.000 0.000 auto -> 0.4119653626888764
437/870 1000 15 14 0.000 1.000 0.000 sqrt -> 0.416905637211217
438/870 1000 15 14 0.000 1.000 0.000 log2 -> 0.416905637211217
439/870 1000 15 20 0.000 1.000 0.000 auto -> 0.4210968436600912
440/870 1000 15 20 0.000 1.000 0.000 sqrt -> 0.427066516644483
441/870 1000 15 20 0.000 1.000 0.000 log2 -> 0.427066516644483
442/870 1000 15 30 0.000 1.000 0.000 auto -> 0.43343277281194376
443/870 1000 15 30 0.000 1.000 0.000 sqrt -> 0.44092618755775453
444/870 1000 15 30 0.000 1.000 0.000 log2 -> 0.44092618755775453
445/870 1000 15 44 0.000 1.000 0.000 auto -> 0.44664525280434203
446/870 1000 15 44 0.000 1.000 0.000 sqrt -> 0.45292896513386394
447/870 1000 15 44 0.000 1.000 0.000 log2 -> 0.45292896513386394
448/870 1000 15 64 0.000 1.000 0.000 auto -> 0.46071402964415226
449/870 1000 15 64 0.000 1.000 0.000 sqrt -> 0.46705807079782297
450/870 1000 15 64 0.000 1.000 0.000 log2 -> 0.46705807079782297
451/870 1000 16 2 0.000 1.000 0.000 auto -> 0.3913086874382543
452/870 1000 16 2 0.000 1.000 0.000 sqrt -> 0.38861990499105653
453/870 1000 16 2 0.000 1.000 0.000 log2 -> 0.38861990499105653
454/870 1000 16 3 0.000 1.000 0.000 auto -> 0.3925571902238872
455/870 1000 16 3 0.000 1.000 0.000 sqrt -> 0.3913714683844088
456/870 1000 16 3 0.000 1.000 0.000 log2 -> 0.3913714683844088
457/870 1000 16 4 0.000 1.000 0.000 auto -> 0.3940701392531158
458/870 1000 16 4 0.000 1.000 0.000 sqrt -> 0.39268075828466614
459/870 1000 16 4 0.000 1.000 0.000 log2 -> 0.39268075828466614
460/870 1000 16 6 0.000 1.000 0.000 auto -> 0.3975020284752258
461/870 1000 16 6 0.000 1.000 0.000 sqrt -> 0.39770698105724994
462/870 1000 16 6 0.000 1.000 0.000 log2 -> 0.39770698105724994
463/870 1000 16 9 0.000 1.000 0.000 auto -> 0.4024208471499012
464/870 1000 16 9 0.000 1.000 0.000 sqrt -> 0.4054161293481425
465/870 1000 16 9 0.000 1.000 0.000 log2 -> 0.4054161293481425
466/870 1000 16 14 0.000 1.000 0.000 auto -> 0.4113117173748257
467/870 1000 16 14 0.000 1.000 0.000 sqrt -> 0.41529444605316784
468/870 1000 16 14 0.000 1.000 0.000 log2 -> 0.41529444605316784
469/870 1000 16 20 0.000 1.000 0.000 auto -> 0.4205506769564708
470/870 1000 16 20 0.000 1.000 0.000 sqrt -> 0.42698037002752726
471/870 1000 16 20 0.000 1.000 0.000 log2 -> 0.42698037002752737
472/870 1000 16 30 0.000 1.000 0.000 auto -> 0.4331228661862119
473/870 1000 16 30 0.000 1.000 0.000 sqrt -> 0.44044477405579524
474/870 1000 16 30 0.000 1.000 0.000 log2 -> 0.44044477405579524
475/870 1000 16 44 0.000 1.000 0.000 auto -> 0.4464995240139633
476/870 1000 16 44 0.000 1.000 0.000 sqrt -> 0.45282165134122293
477/870 1000 16 44 0.000 1.000 0.000 log2 -> 0.45282165134122293
478/870 1000 16 64 0.000 1.000 0.000 auto -> 0.4606584180530144
479/870 1000 16 64 0.000 1.000 0.000 sqrt -> 0.46706762264050755
480/870 1000 16 64 0.000 1.000 0.000 log2 -> 0.46706762264050755
481/870 1000 17 2 0.000 1.000 0.000 auto -> 0.39116034658226223
482/870 1000 17 2 0.000 1.000 0.000 sqrt -> 0.3874746367958537
483/870 1000 17 2 0.000 1.000 0.000 log2 -> 0.3874746367958537
484/870 1000 17 3 0.000 1.000 0.000 auto -> 0.3920532364864758
485/870 1000 17 3 0.000 1.000 0.000 sqrt -> 0.3896896546335637
486/870 1000 17 3 0.000 1.000 0.000 log2 -> 0.38968965463356375
487/870 1000 17 4 0.000 1.000 0.000 auto -> 0.39370747011852075
488/870 1000 17 4 0.000 1.000 0.000 sqrt -> 0.3926547662683104
489/870 1000 17 4 0.000 1.000 0.000 log2 -> 0.3926547662683104
490/870 1000 17 6 0.000 1.000 0.000 auto -> 0.39676924257554375
491/870 1000 17 6 0.000 1.000 0.000 sqrt -> 0.3971203706652255
492/870 1000 17 6 0.000 1.000 0.000 log2 -> 0.3971203706652255
493/870 1000 17 9 0.000 1.000 0.000 auto -> 0.4021951349931556
494/870 1000 17 9 0.000 1.000 0.000 sqrt -> 0.40338572685820556
495/870 1000 17 9 0.000 1.000 0.000 log2 -> 0.40338572685820556
496/870 1000 17 14 0.000 1.000 0.000 auto -> 0.41094375345451334
497/870 1000 17 14 0.000 1.000 0.000 sqrt -> 0.4148821295196692
498/870 1000 17 14 0.000 1.000 0.000 log2 -> 0.4148821295196692
499/870 1000 17 20 0.000 1.000 0.000 auto -> 0.420119032553075
500/870 1000 17 20 0.000 1.000 0.000 sqrt -> 0.42665570800799096
501/870 1000 17 20 0.000 1.000 0.000 log2 -> 0.42665570800799096
502/870 1000 17 30 0.000 1.000 0.000 auto -> 0.4329046876736213
503/870 1000 17 30 0.000 1.000 0.000 sqrt -> 0.4400304917368994
504/870 1000 17 30 0.000 1.000 0.000 log2 -> 0.4400304917368994
505/870 1000 17 44 0.000 1.000 0.000 auto -> 0.44638655739663385
506/870 1000 17 44 0.000 1.000 0.000 sqrt -> 0.4526826013916498
507/870 1000 17 44 0.000 1.000 0.000 log2 -> 0.4526826013916498
508/870 1000 17 64 0.000 1.000 0.000 auto -> 0.4606319569783032
509/870 1000 17 64 0.000 1.000 0.000 sqrt -> 0.46700284208514886
510/870 1000 17 64 0.000 1.000 0.000 log2 -> 0.46700284208514886
511/870 1000 18 2 0.000 1.000 0.000 auto -> 0.38997501151208924
512/870 1000 18 2 0.000 1.000 0.000 sqrt -> 0.3868825926124692
513/870 1000 18 2 0.000 1.000 0.000 log2 -> 0.3868825926124692
514/870 1000 18 3 0.000 1.000 0.000 auto -> 0.3912894220470012
515/870 1000 18 3 0.000 1.000 0.000 sqrt -> 0.3897573115882802
516/870 1000 18 3 0.000 1.000 0.000 log2 -> 0.3897573115882802
517/870 1000 18 4 0.000 1.000 0.000 auto -> 0.39365569829242736
518/870 1000 18 4 0.000 1.000 0.000 sqrt -> 0.390880554872733
519/870 1000 18 4 0.000 1.000 0.000 log2 -> 0.39088055487273293
520/870 1000 18 6 0.000 1.000 0.000 auto -> 0.3966318950232484
521/870 1000 18 6 0.000 1.000 0.000 sqrt -> 0.3954684885602282
522/870 1000 18 6 0.000 1.000 0.000 log2 -> 0.39546848856022826
523/870 1000 18 9 0.000 1.000 0.000 auto -> 0.4019993966281783
524/870 1000 18 9 0.000 1.000 0.000 sqrt -> 0.4035057559800785
525/870 1000 18 9 0.000 1.000 0.000 log2 -> 0.4035057559800785
526/870 1000 18 14 0.000 1.000 0.000 auto -> 0.4106753119751945
527/870 1000 18 14 0.000 1.000 0.000 sqrt -> 0.41456227423880243
528/870 1000 18 14 0.000 1.000 0.000 log2 -> 0.41456227423880243
529/870 1000 18 20 0.000 1.000 0.000 auto -> 0.41995416083899945
530/870 1000 18 20 0.000 1.000 0.000 sqrt -> 0.4262091670385173
531/870 1000 18 20 0.000 1.000 0.000 log2 -> 0.4262091670385173
532/870 1000 18 30 0.000 1.000 0.000 auto -> 0.43279219941157293
533/870 1000 18 30 0.000 1.000 0.000 sqrt -> 0.43993537429299795
534/870 1000 18 30 0.000 1.000 0.000 log2 -> 0.43993537429299784
535/870 1000 18 44 0.000 1.000 0.000 auto -> 0.44636973287956017
536/870 1000 18 44 0.000 1.000 0.000 sqrt -> 0.4525895363967974
537/870 1000 18 44 0.000 1.000 0.000 log2 -> 0.4525895363967974
538/870 1000 18 64 0.000 1.000 0.000 auto -> 0.46062786887368784
539/870 1000 18 64 0.000 1.000 0.000 sqrt -> 0.46696372649876944
540/870 1000 18 64 0.000 1.000 0.000 log2 -> 0.46696372649876944
541/870 1000 19 2 0.000 1.000 0.000 auto -> 0.3900423643092834
542/870 1000 19 2 0.000 1.000 0.000 sqrt -> 0.38593174825931725
543/870 1000 19 2 0.000 1.000 0.000 log2 -> 0.38593174825931725
544/870 1000 19 3 0.000 1.000 0.000 auto -> 0.39135415490583864
545/870 1000 19 3 0.000 1.000 0.000 sqrt -> 0.38958942001042285
546/870 1000 19 3 0.000 1.000 0.000 log2 -> 0.3895894200104228
547/870 1000 19 4 0.000 1.000 0.000 auto -> 0.3930688100034884
548/870 1000 19 4 0.000 1.000 0.000 sqrt -> 0.3902680855135909
549/870 1000 19 4 0.000 1.000 0.000 log2 -> 0.3902680855135909
550/870 1000 19 6 0.000 1.000 0.000 auto -> 0.3964707544328568
551/870 1000 19 6 0.000 1.000 0.000 sqrt -> 0.39530778246311354
552/870 1000 19 6 0.000 1.000 0.000 log2 -> 0.39530778246311354
553/870 1000 19 9 0.000 1.000 0.000 auto -> 0.40156157448076146
554/870 1000 19 9 0.000 1.000 0.000 sqrt -> 0.403610308324132
555/870 1000 19 9 0.000 1.000 0.000 log2 -> 0.403610308324132
556/870 1000 19 14 0.000 1.000 0.000 auto -> 0.4104831235181348
557/870 1000 19 14 0.000 1.000 0.000 sqrt -> 0.4144413959888067
558/870 1000 19 14 0.000 1.000 0.000 log2 -> 0.4144413959888067
559/870 1000 19 20 0.000 1.000 0.000 auto -> 0.41992467920842874
560/870 1000 19 20 0.000 1.000 0.000 sqrt -> 0.426189780100706
561/870 1000 19 20 0.000 1.000 0.000 log2 -> 0.42618978010070613
562/870 1000 19 30 0.000 1.000 0.000 auto -> 0.4327162398596999
563/870 1000 19 30 0.000 1.000 0.000 sqrt -> 0.4398924817861092
564/870 1000 19 30 0.000 1.000 0.000 log2 -> 0.4398924817861092
565/870 1000 19 44 0.000 1.000 0.000 auto -> 0.4463530027969043
566/870 1000 19 44 0.000 1.000 0.000 sqrt -> 0.45253807502587895
567/870 1000 19 44 0.000 1.000 0.000 log2 -> 0.45253807502587895
568/870 1000 19 64 0.000 1.000 0.000 auto -> 0.4606112359662608
569/870 1000 19 64 0.000 1.000 0.000 sqrt -> 0.4669710517450624
570/870 1000 19 64 0.000 1.000 0.000 log2 -> 0.4669710517450624
571/870 1000 20 2 0.000 1.000 0.000 auto -> 0.3897587709874692
572/870 1000 20 2 0.000 1.000 0.000 sqrt -> 0.385514919205521
573/870 1000 20 2 0.000 1.000 0.000 log2 -> 0.385514919205521
574/870 1000 20 3 0.000 1.000 0.000 auto -> 0.3913309507240205
575/870 1000 20 3 0.000 1.000 0.000 sqrt -> 0.3882047761550537
576/870 1000 20 3 0.000 1.000 0.000 log2 -> 0.3882047761550537
577/870 1000 20 4 0.000 1.000 0.000 auto -> 0.3928198007198609
578/870 1000 20 4 0.000 1.000 0.000 sqrt -> 0.3911101376530192
579/870 1000 20 4 0.000 1.000 0.000 log2 -> 0.3911101376530192
580/870 1000 20 6 0.000 1.000 0.000 auto -> 0.39632987354599686
581/870 1000 20 6 0.000 1.000 0.000 sqrt -> 0.39487029700230947
582/870 1000 20 6 0.000 1.000 0.000 log2 -> 0.39487029700230947
583/870 1000 20 9 0.000 1.000 0.000 auto -> 0.40140629574697356
584/870 1000 20 9 0.000 1.000 0.000 sqrt -> 0.4037487318686761
585/870 1000 20 9 0.000 1.000 0.000 log2 -> 0.4037487318686761
586/870 1000 20 14 0.000 1.000 0.000 auto -> 0.4103586163813509
587/870 1000 20 14 0.000 1.000 0.000 sqrt -> 0.41444489538018764
588/870 1000 20 14 0.000 1.000 0.000 log2 -> 0.41444489538018764
589/870 1000 20 20 0.000 1.000 0.000 auto -> 0.41981040039740974
590/870 1000 20 20 0.000 1.000 0.000 sqrt -> 0.4259516601690337
591/870 1000 20 20 0.000 1.000 0.000 log2 -> 0.42595166016903363
592/870 1000 20 30 0.000 1.000 0.000 auto -> 0.432637161960751
593/870 1000 20 30 0.000 1.000 0.000 sqrt -> 0.43973315026372856
594/870 1000 20 30 0.000 1.000 0.000 log2 -> 0.43973315026372856
595/870 1000 20 44 0.000 1.000 0.000 auto -> 0.4463309173881609
596/870 1000 20 44 0.000 1.000 0.000 sqrt -> 0.4525164190199344
597/870 1000 20 44 0.000 1.000 0.000 log2 -> 0.4525164190199344
598/870 1000 20 64 0.000 1.000 0.000 auto -> 0.4606137395342445
599/870 1000 20 64 0.000 1.000 0.000 sqrt -> 0.46697022178673103
600/870 1000 20 64 0.000 1.000 0.000 log2 -> 0.46697022178673103
601/870 1000 21 2 0.000 1.000 0.000 auto -> 0.38994714981806006
602/870 1000 21 2 0.000 1.000 0.000 sqrt -> 0.38578981509071303
603/870 1000 21 2 0.000 1.000 0.000 log2 -> 0.38578981509071303
604/870 1000 21 3 0.000 1.000 0.000 auto -> 0.39109818994163364
605/870 1000 21 3 0.000 1.000 0.000 sqrt -> 0.38871074793829613
606/870 1000 21 3 0.000 1.000 0.000 log2 -> 0.38871074793829613
607/870 1000 21 4 0.000 1.000 0.000 auto -> 0.3925264804218711
608/870 1000 21 4 0.000 1.000 0.000 sqrt -> 0.39127586946255627
609/870 1000 21 4 0.000 1.000 0.000 log2 -> 0.39127586946255627
610/870 1000 21 6 0.000 1.000 0.000 auto -> 0.3961474109529524
611/870 1000 21 6 0.000 1.000 0.000 sqrt -> 0.39507082244507297
612/870 1000 21 6 0.000 1.000 0.000 log2 -> 0.39507082244507297
613/870 1000 21 9 0.000 1.000 0.000 auto -> 0.40145262366499274
614/870 1000 21 9 0.000 1.000 0.000 sqrt -> 0.4038913921300878
615/870 1000 21 9 0.000 1.000 0.000 log2 -> 0.4038913921300879
616/870 1000 21 14 0.000 1.000 0.000 auto -> 0.41029181080146476
617/870 1000 21 14 0.000 1.000 0.000 sqrt -> 0.41423809096339737
618/870 1000 21 14 0.000 1.000 0.000 log2 -> 0.41423809096339737
619/870 1000 21 20 0.000 1.000 0.000 auto -> 0.4197894182080024
620/870 1000 21 20 0.000 1.000 0.000 sqrt -> 0.4262015009211102
621/870 1000 21 20 0.000 1.000 0.000 log2 -> 0.4262015009211102
622/870 1000 21 30 0.000 1.000 0.000 auto -> 0.4326293197463076
623/870 1000 21 30 0.000 1.000 0.000 sqrt -> 0.4396969837371896
624/870 1000 21 30 0.000 1.000 0.000 log2 -> 0.4396969837371895
625/870 1000 21 44 0.000 1.000 0.000 auto -> 0.44633063953654034
626/870 1000 21 44 0.000 1.000 0.000 sqrt -> 0.4524702264945953
627/870 1000 21 44 0.000 1.000 0.000 log2 -> 0.4524702264945953
628/870 1000 21 64 0.000 1.000 0.000 auto -> 0.46061421474308656
629/870 1000 21 64 0.000 1.000 0.000 sqrt -> 0.4669855194373558
630/870 1000 21 64 0.000 1.000 0.000 log2 -> 0.4669855194373558
631/870 1000 22 2 0.000 1.000 0.000 auto -> 0.38996881068338435
632/870 1000 22 2 0.000 1.000 0.000 sqrt -> 0.38471068976628625
633/870 1000 22 2 0.000 1.000 0.000 log2 -> 0.38471068976628625
634/870 1000 22 3 0.000 1.000 0.000 auto -> 0.3913792293230567
635/870 1000 22 3 0.000 1.000 0.000 sqrt -> 0.3889082241808812
636/870 1000 22 3 0.000 1.000 0.000 log2 -> 0.38890822418088117
637/870 1000 22 4 0.000 1.000 0.000 auto -> 0.3925545450833039
638/870 1000 22 4 0.000 1.000 0.000 sqrt -> 0.3905967899199562
639/870 1000 22 4 0.000 1.000 0.000 log2 -> 0.3905967899199562
640/870 1000 22 6 0.000 1.000 0.000 auto -> 0.3960610183285384
641/870 1000 22 6 0.000 1.000 0.000 sqrt -> 0.3948227490901591
642/870 1000 22 6 0.000 1.000 0.000 log2 -> 0.3948227490901591
643/870 1000 22 9 0.000 1.000 0.000 auto -> 0.4013933881600537
644/870 1000 22 9 0.000 1.000 0.000 sqrt -> 0.403685498093064
645/870 1000 22 9 0.000 1.000 0.000 log2 -> 0.403685498093064
646/870 1000 22 14 0.000 1.000 0.000 auto -> 0.4102880519373029
647/870 1000 22 14 0.000 1.000 0.000 sqrt -> 0.41435411292999663
648/870 1000 22 14 0.000 1.000 0.000 log2 -> 0.41435411292999663
649/870 1000 22 20 0.000 1.000 0.000 auto -> 0.41977270745142786
650/870 1000 22 20 0.000 1.000 0.000 sqrt -> 0.4262967086446378
651/870 1000 22 20 0.000 1.000 0.000 log2 -> 0.42629670864463787
652/870 1000 22 30 0.000 1.000 0.000 auto -> 0.432623085048089
653/870 1000 22 30 0.000 1.000 0.000 sqrt -> 0.4397356703137847
654/870 1000 22 30 0.000 1.000 0.000 log2 -> 0.43973567031378463
655/870 1000 22 44 0.000 1.000 0.000 auto -> 0.44632367786177896
656/870 1000 22 44 0.000 1.000 0.000 sqrt -> 0.45251188748617494
657/870 1000 22 44 0.000 1.000 0.000 log2 -> 0.45251188748617494
658/870 1000 22 64 0.000 1.000 0.000 auto -> 0.4606170800650649
659/870 1000 22 64 0.000 1.000 0.000 sqrt -> 0.46695782394098373
660/870 1000 22 64 0.000 1.000 0.000 log2 -> 0.46695782394098373
661/870 1000 23 2 0.000 1.000 0.000 auto -> 0.3898158479317166
662/870 1000 23 2 0.000 1.000 0.000 sqrt -> 0.3843721213738536
663/870 1000 23 2 0.000 1.000 0.000 log2 -> 0.3843721213738536
664/870 1000 23 3 0.000 1.000 0.000 auto -> 0.39130257396340484
665/870 1000 23 3 0.000 1.000 0.000 sqrt -> 0.3889842917118757
666/870 1000 23 3 0.000 1.000 0.000 log2 -> 0.3889842917118757
667/870 1000 23 4 0.000 1.000 0.000 auto -> 0.3924742670788248
668/870 1000 23 4 0.000 1.000 0.000 sqrt -> 0.39076489611195714
669/870 1000 23 4 0.000 1.000 0.000 log2 -> 0.39076489611195714
670/870 1000 23 6 0.000 1.000 0.000 auto -> 0.3959587092180478
671/870 1000 23 6 0.000 1.000 0.000 sqrt -> 0.3950434735997807
672/870 1000 23 6 0.000 1.000 0.000 log2 -> 0.3950434735997807
673/870 1000 23 9 0.000 1.000 0.000 auto -> 0.4014057429944465
674/870 1000 23 9 0.000 1.000 0.000 sqrt -> 0.40353829448549466
675/870 1000 23 9 0.000 1.000 0.000 log2 -> 0.40353829448549466
676/870 1000 23 14 0.000 1.000 0.000 auto -> 0.4103011893273197
677/870 1000 23 14 0.000 1.000 0.000 sqrt -> 0.41432498260374534
678/870 1000 23 14 0.000 1.000 0.000 log2 -> 0.4143249826037454
679/870 1000 23 20 0.000 1.000 0.000 auto -> 0.4197466751080612
680/870 1000 23 20 0.000 1.000 0.000 sqrt -> 0.42618872943565655
681/870 1000 23 20 0.000 1.000 0.000 log2 -> 0.4261887294356566
682/870 1000 23 30 0.000 1.000 0.000 auto -> 0.4326252178226005
683/870 1000 23 30 0.000 1.000 0.000 sqrt -> 0.43971026305141553
684/870 1000 23 30 0.000 1.000 0.000 log2 -> 0.43971026305141553
685/870 1000 23 44 0.000 1.000 0.000 auto -> 0.44631959262401616
686/870 1000 23 44 0.000 1.000 0.000 sqrt -> 0.452506520356785
687/870 1000 23 44 0.000 1.000 0.000 log2 -> 0.452506520356785
688/870 1000 23 64 0.000 1.000 0.000 auto -> 0.46061722823965034
689/870 1000 23 64 0.000 1.000 0.000 sqrt -> 0.4669430936662897
690/870 1000 23 64 0.000 1.000 0.000 log2 -> 0.4669430936662897
691/870 1000 24 2 0.000 1.000 0.000 auto -> 0.38974854247088286
692/870 1000 24 2 0.000 1.000 0.000 sqrt -> 0.3850558534848127
693/870 1000 24 2 0.000 1.000 0.000 log2 -> 0.3850558534848127
694/870 1000 24 3 0.000 1.000 0.000 auto -> 0.39122804681990625
695/870 1000 24 3 0.000 1.000 0.000 sqrt -> 0.3892394143159184
696/870 1000 24 3 0.000 1.000 0.000 log2 -> 0.3892394143159184
697/870 1000 24 4 0.000 1.000 0.000 auto -> 0.39251727402121483
698/870 1000 24 4 0.000 1.000 0.000 sqrt -> 0.39057040513181934
699/870 1000 24 4 0.000 1.000 0.000 log2 -> 0.39057040513181934
700/870 1000 24 6 0.000 1.000 0.000 auto -> 0.39601221411706716
701/870 1000 24 6 0.000 1.000 0.000 sqrt -> 0.3951632782862437
702/870 1000 24 6 0.000 1.000 0.000 log2 -> 0.3951632782862437
703/870 1000 24 9 0.000 1.000 0.000 auto -> 0.40141999028712316
704/870 1000 24 9 0.000 1.000 0.000 sqrt -> 0.4036710759275132
705/870 1000 24 9 0.000 1.000 0.000 log2 -> 0.4036710759275132
706/870 1000 24 14 0.000 1.000 0.000 auto -> 0.4102827581066655
707/870 1000 24 14 0.000 1.000 0.000 sqrt -> 0.4142615449224131
708/870 1000 24 14 0.000 1.000 0.000 log2 -> 0.4142615449224132
709/870 1000 24 20 0.000 1.000 0.000 auto -> 0.4197574171473639
710/870 1000 24 20 0.000 1.000 0.000 sqrt -> 0.42613882975621875
711/870 1000 24 20 0.000 1.000 0.000 log2 -> 0.42613882975621875
712/870 1000 24 30 0.000 1.000 0.000 auto -> 0.43262250564565624
713/870 1000 24 30 0.000 1.000 0.000 sqrt -> 0.4397553520889326
714/870 1000 24 30 0.000 1.000 0.000 log2 -> 0.4397553520889326
715/870 1000 24 44 0.000 1.000 0.000 auto -> 0.44632283035598275
716/870 1000 24 44 0.000 1.000 0.000 sqrt -> 0.4524886752978889
717/870 1000 24 44 0.000 1.000 0.000 log2 -> 0.4524886752978887
718/870 1000 24 64 0.000 1.000 0.000 auto -> 0.46061721761673063
719/870 1000 24 64 0.000 1.000 0.000 sqrt -> 0.46694267536355555
720/870 1000 24 64 0.000 1.000 0.000 log2 -> 0.4669426753635555
721/870 1000 25 2 0.000 1.000 0.000 auto -> 0.38968425022605907
722/870 1000 25 2 0.000 1.000 0.000 sqrt -> 0.3850115875244529
723/870 1000 25 2 0.000 1.000 0.000 log2 -> 0.3850115875244529
724/870 1000 25 3 0.000 1.000 0.000 auto -> 0.3910948520505328
725/870 1000 25 3 0.000 1.000 0.000 sqrt -> 0.3891794709579009
726/870 1000 25 3 0.000 1.000 0.000 log2 -> 0.3891794709579009
727/870 1000 25 4 0.000 1.000 0.000 auto -> 0.3925625098138548
728/870 1000 25 4 0.000 1.000 0.000 sqrt -> 0.39045491363897544
729/870 1000 25 4 0.000 1.000 0.000 log2 -> 0.3904549136389754
730/870 1000 25 6 0.000 1.000 0.000 auto -> 0.396029860871788
731/870 1000 25 6 0.000 1.000 0.000 sqrt -> 0.3950810358359464
732/870 1000 25 6 0.000 1.000 0.000 log2 -> 0.3950810358359464
733/870 1000 25 9 0.000 1.000 0.000 auto -> 0.4014056462608238
734/870 1000 25 9 0.000 1.000 0.000 sqrt -> 0.40361915330352893
735/870 1000 25 9 0.000 1.000 0.000 log2 -> 0.40361915330352893
736/870 1000 25 14 0.000 1.000 0.000 auto -> 0.41027783967354264
737/870 1000 25 14 0.000 1.000 0.000 sqrt -> 0.414205380772142
738/870 1000 25 14 0.000 1.000 0.000 log2 -> 0.414205380772142
739/870 1000 25 20 0.000 1.000 0.000 auto -> 0.4197731822580802
740/870 1000 25 20 0.000 1.000 0.000 sqrt -> 0.42615044921954587
741/870 1000 25 20 0.000 1.000 0.000 log2 -> 0.42615044921954587
742/870 1000 25 30 0.000 1.000 0.000 auto -> 0.4326229064537255
743/870 1000 25 30 0.000 1.000 0.000 sqrt -> 0.43972253467001504
744/870 1000 25 30 0.000 1.000 0.000 log2 -> 0.43972253467001504
745/870 1000 25 44 0.000 1.000 0.000 auto -> 0.4463219566964705
746/870 1000 25 44 0.000 1.000 0.000 sqrt -> 0.4524919238511911
747/870 1000 25 44 0.000 1.000 0.000 log2 -> 0.4524919238511911
748/870 1000 25 64 0.000 1.000 0.000 auto -> 0.4606186652991498
749/870 1000 25 64 0.000 1.000 0.000 sqrt -> 0.4669534442750258
750/870 1000 25 64 0.000 1.000 0.000 log2 -> 0.4669534442750258
751/870 1000 26 2 0.000 1.000 0.000 auto -> 0.3897062470289309
752/870 1000 26 2 0.000 1.000 0.000 sqrt -> 0.3851106871444907
753/870 1000 26 2 0.000 1.000 0.000 log2 -> 0.3851106871444907
754/870 1000 26 3 0.000 1.000 0.000 auto -> 0.39106598565370426
755/870 1000 26 3 0.000 1.000 0.000 sqrt -> 0.3891070864636961
756/870 1000 26 3 0.000 1.000 0.000 log2 -> 0.3891070864636961
757/870 1000 26 4 0.000 1.000 0.000 auto -> 0.39253910329151404
758/870 1000 26 4 0.000 1.000 0.000 sqrt -> 0.39044909044385195
759/870 1000 26 4 0.000 1.000 0.000 log2 -> 0.39044909044385195
760/870 1000 26 6 0.000 1.000 0.000 auto -> 0.3960242767814833
761/870 1000 26 6 0.000 1.000 0.000 sqrt -> 0.3951368784728062
762/870 1000 26 6 0.000 1.000 0.000 log2 -> 0.3951368784728062
763/870 1000 26 9 0.000 1.000 0.000 auto -> 0.40140337581650415
764/870 1000 26 9 0.000 1.000 0.000 sqrt -> 0.4036105560231418
765/870 1000 26 9 0.000 1.000 0.000 log2 -> 0.4036105560231418
766/870 1000 26 14 0.000 1.000 0.000 auto -> 0.41027916023814054
767/870 1000 26 14 0.000 1.000 0.000 sqrt -> 0.41416186251401116
768/870 1000 26 14 0.000 1.000 0.000 log2 -> 0.4141618625140111
769/870 1000 26 20 0.000 1.000 0.000 auto -> 0.41977053794682456
770/870 1000 26 20 0.000 1.000 0.000 sqrt -> 0.42617048328123586
771/870 1000 26 20 0.000 1.000 0.000 log2 -> 0.4261704832812358
772/870 1000 26 30 0.000 1.000 0.000 auto -> 0.4326236358434836
773/870 1000 26 30 0.000 1.000 0.000 sqrt -> 0.43970234189400076
774/870 1000 26 30 0.000 1.000 0.000 log2 -> 0.43970234189400087
775/870 1000 26 44 0.000 1.000 0.000 auto -> 0.44632408107449106
776/870 1000 26 44 0.000 1.000 0.000 sqrt -> 0.4524911229847907
777/870 1000 26 44 0.000 1.000 0.000 log2 -> 0.4524911229847906
778/870 1000 26 64 0.000 1.000 0.000 auto -> 0.46061982982202926
779/870 1000 26 64 0.000 1.000 0.000 sqrt -> 0.46695187800449256
780/870 1000 26 64 0.000 1.000 0.000 log2 -> 0.46695187800449256
781/870 1000 27 2 0.000 1.000 0.000 auto -> 0.3896424911332597
782/870 1000 27 2 0.000 1.000 0.000 sqrt -> 0.38505253732799055
783/870 1000 27 2 0.000 1.000 0.000 log2 -> 0.38505253732799055
784/870 1000 27 3 0.000 1.000 0.000 auto -> 0.39108070590121596
785/870 1000 27 3 0.000 1.000 0.000 sqrt -> 0.389242038929196
786/870 1000 27 3 0.000 1.000 0.000 log2 -> 0.389242038929196
787/870 1000 27 4 0.000 1.000 0.000 auto -> 0.3925592407925665
788/870 1000 27 4 0.000 1.000 0.000 sqrt -> 0.39043200581025445
789/870 1000 27 4 0.000 1.000 0.000 log2 -> 0.39043200581025445
790/870 1000 27 6 0.000 1.000 0.000 auto -> 0.3960255514386031
791/870 1000 27 6 0.000 1.000 0.000 sqrt -> 0.39514446139855225
792/870 1000 27 6 0.000 1.000 0.000 log2 -> 0.39514446139855225
793/870 1000 27 9 0.000 1.000 0.000 auto -> 0.4014065642844778
794/870 1000 27 9 0.000 1.000 0.000 sqrt -> 0.40359989729454887
795/870 1000 27 9 0.000 1.000 0.000 log2 -> 0.40359989729454876
796/870 1000 27 14 0.000 1.000 0.000 auto -> 0.41027107264187723
797/870 1000 27 14 0.000 1.000 0.000 sqrt -> 0.4141458536853008
798/870 1000 27 14 0.000 1.000 0.000 log2 -> 0.4141458536853008
799/870 1000 27 20 0.000 1.000 0.000 auto -> 0.41976529505078664
800/870 1000 27 20 0.000 1.000 0.000 sqrt -> 0.42618492272807235
801/870 1000 27 20 0.000 1.000 0.000 log2 -> 0.42618492272807235
802/870 1000 27 30 0.000 1.000 0.000 auto -> 0.43262296671095424
803/870 1000 27 30 0.000 1.000 0.000 sqrt -> 0.43970182283817333
804/870 1000 27 30 0.000 1.000 0.000 log2 -> 0.43970182283817333
805/870 1000 27 44 0.000 1.000 0.000 auto -> 0.446324108513088
806/870 1000 27 44 0.000 1.000 0.000 sqrt -> 0.4524911229847906
807/870 1000 27 44 0.000 1.000 0.000 log2 -> 0.4524911229847906
808/870 1000 27 64 0.000 1.000 0.000 auto -> 0.46061982982202926
809/870 1000 27 64 0.000 1.000 0.000 sqrt -> 0.46695187800449256
810/870 1000 27 64 0.000 1.000 0.000 log2 -> 0.46695187800449256
811/870 1000 28 2 0.000 1.000 0.000 auto -> 0.3896637705538974
812/870 1000 28 2 0.000 1.000 0.000 sqrt -> 0.38505356367723403
813/870 1000 28 2 0.000 1.000 0.000 log2 -> 0.38505356367723403
814/870 1000 28 3 0.000 1.000 0.000 auto -> 0.3910827696920453
815/870 1000 28 3 0.000 1.000 0.000 sqrt -> 0.38912941057363165
816/870 1000 28 3 0.000 1.000 0.000 log2 -> 0.38912941057363165
817/870 1000 28 4 0.000 1.000 0.000 auto -> 0.39254981807784034
818/870 1000 28 4 0.000 1.000 0.000 sqrt -> 0.390493791297924
819/870 1000 28 4 0.000 1.000 0.000 log2 -> 0.3904937912979239
820/870 1000 28 6 0.000 1.000 0.000 auto -> 0.396022094669372
821/870 1000 28 6 0.000 1.000 0.000 sqrt -> 0.3951726750127878
822/870 1000 28 6 0.000 1.000 0.000 log2 -> 0.3951726750127878
823/870 1000 28 9 0.000 1.000 0.000 auto -> 0.401401150492245
824/870 1000 28 9 0.000 1.000 0.000 sqrt -> 0.40361745999733883
825/870 1000 28 9 0.000 1.000 0.000 log2 -> 0.40361745999733895
826/870 1000 28 14 0.000 1.000 0.000 auto -> 0.41027776351316186
827/870 1000 28 14 0.000 1.000 0.000 sqrt -> 0.41416317093572075
828/870 1000 28 14 0.000 1.000 0.000 log2 -> 0.41416317093572075
829/870 1000 28 20 0.000 1.000 0.000 auto -> 0.4197648115268066
830/870 1000 28 20 0.000 1.000 0.000 sqrt -> 0.42616194007052005
831/870 1000 28 20 0.000 1.000 0.000 log2 -> 0.4261619400705201
832/870 1000 28 30 0.000 1.000 0.000 auto -> 0.43262243384597726
833/870 1000 28 30 0.000 1.000 0.000 sqrt -> 0.43970182283817333
834/870 1000 28 30 0.000 1.000 0.000 log2 -> 0.43970182283817333
835/870 1000 28 44 0.000 1.000 0.000 auto -> 0.44632375792489154
836/870 1000 28 44 0.000 1.000 0.000 sqrt -> 0.4524911229847906
837/870 1000 28 44 0.000 1.000 0.000 log2 -> 0.4524911229847906
838/870 1000 28 64 0.000 1.000 0.000 auto -> 0.46061982982202926
839/870 1000 28 64 0.000 1.000 0.000 sqrt -> 0.46695187800449256
840/870 1000 28 64 0.000 1.000 0.000 log2 -> 0.4669518780044925
841/870 1000 29 2 0.000 1.000 0.000 auto -> 0.3896728060696774
842/870 1000 29 2 0.000 1.000 0.000 sqrt -> 0.38500080900839584
843/870 1000 29 2 0.000 1.000 0.000 log2 -> 0.38500080900839584
844/870 1000 29 3 0.000 1.000 0.000 auto -> 0.3910962025750861
845/870 1000 29 3 0.000 1.000 0.000 sqrt -> 0.3891562040133909
846/870 1000 29 3 0.000 1.000 0.000 log2 -> 0.3891562040133909
847/870 1000 29 4 0.000 1.000 0.000 auto -> 0.39255167928272666
848/870 1000 29 4 0.000 1.000 0.000 sqrt -> 0.39050146879691816
849/870 1000 29 4 0.000 1.000 0.000 log2 -> 0.39050146879691816
850/870 1000 29 6 0.000 1.000 0.000 auto -> 0.39602534828250086
851/870 1000 29 6 0.000 1.000 0.000 sqrt -> 0.3951264819395808
852/870 1000 29 6 0.000 1.000 0.000 log2 -> 0.39512648193958083
853/870 1000 29 9 0.000 1.000 0.000 auto -> 0.40140279079667623
854/870 1000 29 9 0.000 1.000 0.000 sqrt -> 0.4036041303660367
855/870 1000 29 9 0.000 1.000 0.000 log2 -> 0.40360413036603665
856/870 1000 29 14 0.000 1.000 0.000 auto -> 0.41027080485248774
857/870 1000 29 14 0.000 1.000 0.000 sqrt -> 0.4141720207650137
858/870 1000 29 14 0.000 1.000 0.000 log2 -> 0.4141720207650137
859/870 1000 29 20 0.000 1.000 0.000 auto -> 0.4197605101162413
860/870 1000 29 20 0.000 1.000 0.000 sqrt -> 0.42617361421141275
861/870 1000 29 20 0.000 1.000 0.000 log2 -> 0.42617361421141275
862/870 1000 29 30 0.000 1.000 0.000 auto -> 0.4326205413592327
863/870 1000 29 30 0.000 1.000 0.000 sqrt -> 0.43970182283817333
864/870 1000 29 30 0.000 1.000 0.000 log2 -> 0.43970182283817333
865/870 1000 29 44 0.000 1.000 0.000 auto -> 0.4463234986223216
866/870 1000 29 44 0.000 1.000 0.000 sqrt -> 0.4524911229847907
867/870 1000 29 44 0.000 1.000 0.000 log2 -> 0.4524911229847907
868/870 1000 29 64 0.000 1.000 0.000 auto -> 0.46061982982202926
869/870 1000 29 64 0.000 1.000 0.000 sqrt -> 0.46695187800449256
870/870 1000 29 64 0.000 1.000 0.000 log2 -> 0.46695187800449256
Time Taken 5141.224s
train_df, test_df = get_datasets(logarithm=True, feature_selection=True)
X_train = train_df.drop("quality",axis=1).values
X_test = test_df.drop("quality",axis=1).values
y_train = train_df["quality"].values
y_test = test_df["quality"].values
# Avaliable Kernels are {‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’}
train_config = SupportVectorRegressor_train(X_train,y_train,cross_validation=True, kernel = "rbf", test_for_professor = test_for_professor)
df = pd.DataFrame.from_dict(train_config)
df = df.sort_values(by=['mse_val'])
if not test_for_professor:
df.to_csv('results/train_conf_svr_feat_sel.csv',index=False)
1/3780 0.050 0.032 scale StandardScaler() 0 -> 0.5787432849079324
2/3780 0.050 0.032 scale MinMaxScaler() 0 -> 0.5749910230560764
3/3780 0.050 0.032 auto StandardScaler() 0 -> 0.5787432849079449
4/3780 0.050 0.032 auto MinMaxScaler() 0 -> 0.6812117397796916
5/3780 0.050 0.032 0.01 StandardScaler() 0 -> 0.676191344770916
6/3780 0.050 0.032 0.01 MinMaxScaler() 0 -> 0.7451503778890992
7/3780 0.050 0.032 0.03162277660168379 StandardScaler() 0 -> 0.6160805976136176
8/3780 0.050 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7265186614329805
9/3780 0.050 0.032 0.1 StandardScaler() 0 -> 0.5740999404684444
10/3780 0.050 0.032 0.1 MinMaxScaler() 0 -> 0.7024556054607523
11/3780 0.050 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5895977917688922
12/3780 0.050 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6611517368919119
13/3780 0.050 0.032 1.0 StandardScaler() 0 -> 0.6473299063870331
14/3780 0.050 0.032 1.0 MinMaxScaler() 0 -> 0.5992666534925047
15/3780 0.050 0.040 scale StandardScaler() 0 -> 0.571966251585832
16/3780 0.050 0.040 scale MinMaxScaler() 0 -> 0.5679980203102948
17/3780 0.050 0.040 auto StandardScaler() 0 -> 0.5719662515857289
18/3780 0.050 0.040 auto MinMaxScaler() 0 -> 0.6703956220233583
19/3780 0.050 0.040 0.01 StandardScaler() 0 -> 0.6646308144296129
20/3780 0.050 0.040 0.01 MinMaxScaler() 0 -> 0.7420135282011607
21/3780 0.050 0.040 0.03162277660168379 StandardScaler() 0 -> 0.6002143236411074
22/3780 0.050 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7226783831248853
23/3780 0.050 0.040 0.1 StandardScaler() 0 -> 0.5663749651215254
24/3780 0.050 0.040 0.1 MinMaxScaler() 0 -> 0.6956280873830712
25/3780 0.050 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5820995379833214
26/3780 0.050 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.6484738278302593
27/3780 0.050 0.040 1.0 StandardScaler() 0 -> 0.6330299090791504
28/3780 0.050 0.040 1.0 MinMaxScaler() 0 -> 0.5860430577643934
29/3780 0.050 0.051 scale StandardScaler() 0 -> 0.566258753239996
30/3780 0.050 0.051 scale MinMaxScaler() 0 -> 0.56342094508611
31/3780 0.050 0.051 auto StandardScaler() 0 -> 0.5662587532400573
32/3780 0.050 0.051 auto MinMaxScaler() 0 -> 0.6585539713009593
33/3780 0.050 0.051 0.01 StandardScaler() 0 -> 0.6517050079724837
34/3780 0.050 0.051 0.01 MinMaxScaler() 0 -> 0.7381325656707859
35/3780 0.050 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5870090805731348
36/3780 0.050 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7178263436963133
37/3780 0.050 0.051 0.1 StandardScaler() 0 -> 0.5602906546656558
38/3780 0.050 0.051 0.1 MinMaxScaler() 0 -> 0.6878804580075172
39/3780 0.050 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5753810911135203
40/3780 0.050 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.6338511418340568
41/3780 0.050 0.051 1.0 StandardScaler() 0 -> 0.6198472599748984
42/3780 0.050 0.051 1.0 MinMaxScaler() 0 -> 0.576710714781291
43/3780 0.050 0.065 scale StandardScaler() 0 -> 0.5628082895265043
44/3780 0.050 0.065 scale MinMaxScaler() 0 -> 0.5601295490004297
45/3780 0.050 0.065 auto StandardScaler() 0 -> 0.5628082895264231
46/3780 0.050 0.065 auto MinMaxScaler() 0 -> 0.6455246598422542
47/3780 0.050 0.065 0.01 StandardScaler() 0 -> 0.6376819772817987
48/3780 0.050 0.065 0.01 MinMaxScaler() 0 -> 0.7335916905538656
49/3780 0.050 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5773489723405104
50/3780 0.050 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.7128036110439423
51/3780 0.050 0.065 0.1 StandardScaler() 0 -> 0.5562573295529454
52/3780 0.050 0.065 0.1 MinMaxScaler() 0 -> 0.6788240620608724
53/3780 0.050 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5702403350648106
54/3780 0.050 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.6188222424112995
55/3780 0.050 0.065 1.0 StandardScaler() 0 -> 0.607843945793024
56/3780 0.050 0.065 1.0 MinMaxScaler() 0 -> 0.5691138602831788
57/3780 0.050 0.082 scale StandardScaler() 0 -> 0.5601799980747262
58/3780 0.050 0.082 scale MinMaxScaler() 0 -> 0.5582003117315438
59/3780 0.050 0.082 auto StandardScaler() 0 -> 0.5601799980747808
60/3780 0.050 0.082 auto MinMaxScaler() 0 -> 0.6309446028170801
61/3780 0.050 0.082 0.01 StandardScaler() 0 -> 0.6227818563686952
62/3780 0.050 0.082 0.01 MinMaxScaler() 0 -> 0.7294684814161724
63/3780 0.050 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5702667852234563
64/3780 0.050 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.707220749376499
65/3780 0.050 0.082 0.1 StandardScaler() 0 -> 0.5537191724106026
66/3780 0.050 0.082 0.1 MinMaxScaler() 0 -> 0.6680744677458662
67/3780 0.050 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5661683372543688
68/3780 0.050 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.6036301651968506
69/3780 0.050 0.082 1.0 StandardScaler() 0 -> 0.596374723476225
70/3780 0.050 0.082 1.0 MinMaxScaler() 0 -> 0.5615331460755084
71/3780 0.050 0.104 scale StandardScaler() 0 -> 0.5580070287613634
72/3780 0.050 0.104 scale MinMaxScaler() 0 -> 0.5564515069843843
73/3780 0.050 0.104 auto StandardScaler() 0 -> 0.5580070287614373
74/3780 0.050 0.104 auto MinMaxScaler() 0 -> 0.6161654249564088
75/3780 0.050 0.104 0.01 StandardScaler() 0 -> 0.6080316093192845
76/3780 0.050 0.104 0.01 MinMaxScaler() 0 -> 0.7256884297395727
77/3780 0.050 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5630460217748819
78/3780 0.050 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.7008214745005944
79/3780 0.050 0.104 0.1 StandardScaler() 0 -> 0.5526785714304046
80/3780 0.050 0.104 0.1 MinMaxScaler() 0 -> 0.6558245616480888
81/3780 0.050 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5624801890628168
82/3780 0.050 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5922059327761656
83/3780 0.050 0.104 1.0 StandardScaler() 0 -> 0.585701731336736
84/3780 0.050 0.104 1.0 MinMaxScaler() 0 -> 0.5562764542041363
85/3780 0.050 0.132 scale StandardScaler() 0 -> 0.5561560366983023
86/3780 0.050 0.132 scale MinMaxScaler() 0 -> 0.5542223653920385
87/3780 0.050 0.132 auto StandardScaler() 0 -> 0.5561560366983022
88/3780 0.050 0.132 auto MinMaxScaler() 0 -> 0.6023603094949207
89/3780 0.050 0.132 0.01 StandardScaler() 0 -> 0.5960537787456325
90/3780 0.050 0.132 0.01 MinMaxScaler() 0 -> 0.7218356627183976
91/3780 0.050 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5570280714257273
92/3780 0.050 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6936550623565377
93/3780 0.050 0.132 0.1 StandardScaler() 0 -> 0.5519234992045521
94/3780 0.050 0.132 0.1 MinMaxScaler() 0 -> 0.6427407547472873
95/3780 0.050 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5590601009063354
96/3780 0.050 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5846228652004598
97/3780 0.050 0.132 1.0 StandardScaler() 0 -> 0.5765007789116647
98/3780 0.050 0.132 1.0 MinMaxScaler() 0 -> 0.5525580921805281
99/3780 0.050 0.168 scale StandardScaler() 0 -> 0.5543054373313661
100/3780 0.050 0.168 scale MinMaxScaler() 0 -> 0.5524379255975752
101/3780 0.050 0.168 auto StandardScaler() 0 -> 0.5543054373316322
102/3780 0.050 0.168 auto MinMaxScaler() 0 -> 0.592203620141286
103/3780 0.050 0.168 0.01 StandardScaler() 0 -> 0.5874985506034092
104/3780 0.050 0.168 0.01 MinMaxScaler() 0 -> 0.7168450712282382
105/3780 0.050 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5527133615634353
106/3780 0.050 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6857788918008407
107/3780 0.050 0.168 0.1 StandardScaler() 0 -> 0.5510893927794308
108/3780 0.050 0.168 0.1 MinMaxScaler() 0 -> 0.6279802990903319
109/3780 0.050 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5558391574248952
110/3780 0.050 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.579618442298491
111/3780 0.050 0.168 1.0 StandardScaler() 0 -> 0.5681252086921313
112/3780 0.050 0.168 1.0 MinMaxScaler() 0 -> 0.5503433242962376
113/3780 0.050 0.213 scale StandardScaler() 0 -> 0.5527980773017093
114/3780 0.050 0.213 scale MinMaxScaler() 0 -> 0.5509083869616948
115/3780 0.050 0.213 auto StandardScaler() 0 -> 0.552798077301648
116/3780 0.050 0.213 auto MinMaxScaler() 0 -> 0.5864667796100002
117/3780 0.050 0.213 0.01 StandardScaler() 0 -> 0.5821031432357919
118/3780 0.050 0.213 0.01 MinMaxScaler() 0 -> 0.7117600410795148
119/3780 0.050 0.213 0.03162277660168379 StandardScaler() 0 -> 0.549979104692294
120/3780 0.050 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6763731446743787
121/3780 0.050 0.213 0.1 StandardScaler() 0 -> 0.551030694825076
122/3780 0.050 0.213 0.1 MinMaxScaler() 0 -> 0.6134032238690418
123/3780 0.050 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5534557786715428
124/3780 0.050 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.574988515417746
125/3780 0.050 0.213 1.0 StandardScaler() 0 -> 0.5607742770464929
126/3780 0.050 0.213 1.0 MinMaxScaler() 0 -> 0.5486191366243421
127/3780 0.050 0.270 scale StandardScaler() 0 -> 0.551047236202623
128/3780 0.050 0.270 scale MinMaxScaler() 0 -> 0.5495534865650956
129/3780 0.050 0.270 auto StandardScaler() 0 -> 0.5510472362025575
130/3780 0.050 0.270 auto MinMaxScaler() 0 -> 0.5826068509534243
131/3780 0.050 0.270 0.01 StandardScaler() 0 -> 0.5768307656723055
132/3780 0.050 0.270 0.01 MinMaxScaler() 0 -> 0.7062005392925309
133/3780 0.050 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5488508971761731
134/3780 0.050 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6654562755033484
135/3780 0.050 0.270 0.1 StandardScaler() 0 -> 0.5504764370746337
136/3780 0.050 0.270 0.1 MinMaxScaler() 0 -> 0.6011678212748857
137/3780 0.050 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5515805700482108
138/3780 0.050 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5701320859756848
139/3780 0.050 0.270 1.0 StandardScaler() 0 -> 0.5546046046859646
140/3780 0.050 0.270 1.0 MinMaxScaler() 0 -> 0.5488311616098103
141/3780 0.050 0.342 scale StandardScaler() 0 -> 0.5498195308136197
142/3780 0.050 0.342 scale MinMaxScaler() 0 -> 0.5482797080999756
143/3780 0.050 0.342 auto StandardScaler() 0 -> 0.5498195308109999
144/3780 0.050 0.342 auto MinMaxScaler() 0 -> 0.5785826557595483
145/3780 0.050 0.342 0.01 StandardScaler() 0 -> 0.5722538752940388
146/3780 0.050 0.342 0.01 MinMaxScaler() 0 -> 0.6993823954415074
147/3780 0.050 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5479395708535635
148/3780 0.050 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.6528257040902247
149/3780 0.050 0.342 0.1 StandardScaler() 0 -> 0.5502207130134021
150/3780 0.050 0.342 0.1 MinMaxScaler() 0 -> 0.5933369326891708
151/3780 0.050 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5497882751256651
152/3780 0.050 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.565899864810315
153/3780 0.050 0.342 1.0 StandardScaler() 0 -> 0.5504767445272786
154/3780 0.050 0.342 1.0 MinMaxScaler() 0 -> 0.548891676069004
155/3780 0.050 0.434 scale StandardScaler() 0 -> 0.5492835443520722
156/3780 0.050 0.434 scale MinMaxScaler() 0 -> 0.5471684187008864
157/3780 0.050 0.434 auto StandardScaler() 0 -> 0.549283544352209
158/3780 0.050 0.434 auto MinMaxScaler() 0 -> 0.5750441615966486
159/3780 0.050 0.434 0.01 StandardScaler() 0 -> 0.5681894860833345
160/3780 0.050 0.434 0.01 MinMaxScaler() 0 -> 0.6924393317428045
161/3780 0.050 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5482817397413683
162/3780 0.050 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.6389810991729529
163/3780 0.050 0.434 0.1 StandardScaler() 0 -> 0.5499845852605857
164/3780 0.050 0.434 0.1 MinMaxScaler() 0 -> 0.5887825798299327
165/3780 0.050 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5485243803125791
166/3780 0.050 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.560931180906139
167/3780 0.050 0.434 1.0 StandardScaler() 0 -> 0.5488662426826477
168/3780 0.050 0.434 1.0 MinMaxScaler() 0 -> 0.5489857617257113
169/3780 0.050 0.551 scale StandardScaler() 0 -> 0.5484477191603055
170/3780 0.050 0.551 scale MinMaxScaler() 0 -> 0.5461552916503362
171/3780 0.050 0.551 auto StandardScaler() 0 -> 0.5484477191603057
172/3780 0.050 0.551 auto MinMaxScaler() 0 -> 0.571366172786405
173/3780 0.050 0.551 0.01 StandardScaler() 0 -> 0.5633595401394073
174/3780 0.050 0.551 0.01 MinMaxScaler() 0 -> 0.6842660295678877
175/3780 0.050 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5481706515078364
176/3780 0.050 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.6248983563201174
177/3780 0.050 0.551 0.1 StandardScaler() 0 -> 0.5495105889418405
178/3780 0.050 0.551 0.1 MinMaxScaler() 0 -> 0.5860027255093416
179/3780 0.050 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5475377498107571
180/3780 0.050 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5564641886801875
181/3780 0.050 0.551 1.0 StandardScaler() 0 -> 0.5480125856420445
182/3780 0.050 0.551 1.0 MinMaxScaler() 0 -> 0.5488337328695033
183/3780 0.050 0.700 scale StandardScaler() 0 -> 0.5476975937000449
184/3780 0.050 0.700 scale MinMaxScaler() 0 -> 0.5454163332417443
185/3780 0.050 0.700 auto StandardScaler() 0 -> 0.5476975937022198
186/3780 0.050 0.700 auto MinMaxScaler() 0 -> 0.5674270505549671
187/3780 0.050 0.700 0.01 StandardScaler() 0 -> 0.5589391733966652
188/3780 0.050 0.700 0.01 MinMaxScaler() 0 -> 0.6741823272595688
189/3780 0.050 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5480966518487022
190/3780 0.050 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.6108739021329698
191/3780 0.050 0.700 0.1 StandardScaler() 0 -> 0.5489907590838015
192/3780 0.050 0.700 0.1 MinMaxScaler() 0 -> 0.5834506491060482
193/3780 0.050 0.700 0.31622776601683794 StandardScaler() 0 -> 0.546777154794548
194/3780 0.050 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5534905482706677
195/3780 0.050 0.700 1.0 StandardScaler() 0 -> 0.5494068286451359
196/3780 0.050 0.700 1.0 MinMaxScaler() 0 -> 0.5492761557397401
197/3780 0.050 0.888 scale StandardScaler() 0 -> 0.5468716769365259
198/3780 0.050 0.888 scale MinMaxScaler() 0 -> 0.5448562203754336
199/3780 0.050 0.888 auto StandardScaler() 0 -> 0.5468716769365256
200/3780 0.050 0.888 auto MinMaxScaler() 0 -> 0.5632241460921966
201/3780 0.050 0.888 0.01 StandardScaler() 0 -> 0.5550659748543749
202/3780 0.050 0.888 0.01 MinMaxScaler() 0 -> 0.6632996052503817
203/3780 0.050 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5490266968252299
204/3780 0.050 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5995874257496939
205/3780 0.050 0.888 0.1 StandardScaler() 0 -> 0.5486753845086476
206/3780 0.050 0.888 0.1 MinMaxScaler() 0 -> 0.5812951702519262
207/3780 0.050 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5471961033606138
208/3780 0.050 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5517327029023432
209/3780 0.050 0.888 1.0 StandardScaler() 0 -> 0.5541135039404456
210/3780 0.050 0.888 1.0 MinMaxScaler() 0 -> 0.5493420550701312
211/3780 0.050 1.126 scale StandardScaler() 0 -> 0.5473283363103696
212/3780 0.050 1.126 scale MinMaxScaler() 0 -> 0.5443575036264515
213/3780 0.050 1.126 auto StandardScaler() 0 -> 0.5473283363084631
214/3780 0.050 1.126 auto MinMaxScaler() 0 -> 0.5590378421210453
215/3780 0.050 1.126 0.01 StandardScaler() 0 -> 0.5525849697491002
216/3780 0.050 1.126 0.01 MinMaxScaler() 0 -> 0.6503630160561605
217/3780 0.050 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5490682248273185
218/3780 0.050 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.593996636381438
219/3780 0.050 1.126 0.1 StandardScaler() 0 -> 0.5488801196940751
220/3780 0.050 1.126 0.1 MinMaxScaler() 0 -> 0.579035752265042
221/3780 0.050 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5488889703964509
222/3780 0.050 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5509853569116955
223/3780 0.050 1.126 1.0 StandardScaler() 0 -> 0.5609323675589378
224/3780 0.050 1.126 1.0 MinMaxScaler() 0 -> 0.5495079747173262
225/3780 0.050 1.429 scale StandardScaler() 0 -> 0.5485106644237613
226/3780 0.050 1.429 scale MinMaxScaler() 0 -> 0.5448786209671368
227/3780 0.050 1.429 auto StandardScaler() 0 -> 0.548501942402054
228/3780 0.050 1.429 auto MinMaxScaler() 0 -> 0.5552863448965566
229/3780 0.050 1.429 0.01 StandardScaler() 0 -> 0.5506595720062927
230/3780 0.050 1.429 0.01 MinMaxScaler() 0 -> 0.6360729232069181
231/3780 0.050 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5489811019145666
232/3780 0.050 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5909692581416012
233/3780 0.050 1.429 0.1 StandardScaler() 0 -> 0.5485170711265323
234/3780 0.050 1.429 0.1 MinMaxScaler() 0 -> 0.5762387697657942
235/3780 0.050 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5508849003739231
236/3780 0.050 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5501609433798423
237/3780 0.050 1.429 1.0 StandardScaler() 0 -> 0.5693623809108382
238/3780 0.050 1.429 1.0 MinMaxScaler() 0 -> 0.5496525330627855
239/3780 0.050 1.814 scale StandardScaler() 0 -> 0.5496460408731769
240/3780 0.050 1.814 scale MinMaxScaler() 0 -> 0.5456527438520732
241/3780 0.050 1.814 auto StandardScaler() 0 -> 0.5496320714925446
242/3780 0.050 1.814 auto MinMaxScaler() 0 -> 0.5526901686464298
243/3780 0.050 1.814 0.01 StandardScaler() 0 -> 0.5501000888462003
244/3780 0.050 1.814 0.01 MinMaxScaler() 0 -> 0.62229506011733
245/3780 0.050 1.814 0.03162277660168379 StandardScaler() 0 -> 0.549378201759574
246/3780 0.050 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5894636964666685
247/3780 0.050 1.814 0.1 StandardScaler() 0 -> 0.5486432420322518
248/3780 0.050 1.814 0.1 MinMaxScaler() 0 -> 0.5728620412299964
249/3780 0.050 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5537323230628927
250/3780 0.050 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5502202002544646
251/3780 0.050 1.814 1.0 StandardScaler() 0 -> 0.5799035825936772
252/3780 0.050 1.814 1.0 MinMaxScaler() 0 -> 0.5497408198444443
253/3780 0.050 2.302 scale StandardScaler() 0 -> 0.5518602872832716
254/3780 0.050 2.302 scale MinMaxScaler() 0 -> 0.547789047068399
255/3780 0.050 2.302 auto StandardScaler() 0 -> 0.551860287268556
256/3780 0.050 2.302 auto MinMaxScaler() 0 -> 0.551862336469921
257/3780 0.050 2.302 0.01 StandardScaler() 0 -> 0.5499461807177964
258/3780 0.050 2.302 0.01 MinMaxScaler() 0 -> 0.6088000612307406
259/3780 0.050 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5489751184657948
260/3780 0.050 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5881084146630259
261/3780 0.050 2.302 0.1 StandardScaler() 0 -> 0.5491374535310513
262/3780 0.050 2.302 0.1 MinMaxScaler() 0 -> 0.5693711203001013
263/3780 0.050 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5575262334828323
264/3780 0.050 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5506934370081661
265/3780 0.050 2.302 1.0 StandardScaler() 0 -> 0.5919297334941321
266/3780 0.050 2.302 1.0 MinMaxScaler() 0 -> 0.5496303974558917
267/3780 0.050 2.921 scale StandardScaler() 0 -> 0.5546017244691231
268/3780 0.050 2.921 scale MinMaxScaler() 0 -> 0.5496810577448117
269/3780 0.050 2.921 auto StandardScaler() 0 -> 0.5546018643978613
270/3780 0.050 2.921 auto MinMaxScaler() 0 -> 0.5511183171933823
271/3780 0.050 2.921 0.01 StandardScaler() 0 -> 0.550030914050211
272/3780 0.050 2.921 0.01 MinMaxScaler() 0 -> 0.5982762182786501
273/3780 0.050 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5487953234290286
274/3780 0.050 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5872448534931025
275/3780 0.050 2.921 0.1 StandardScaler() 0 -> 0.5484959562070965
276/3780 0.050 2.921 0.1 MinMaxScaler() 0 -> 0.565373399867049
277/3780 0.050 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5622490264203533
278/3780 0.050 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5508321316909034
279/3780 0.050 2.921 1.0 StandardScaler() 0 -> 0.607273097738402
280/3780 0.050 2.921 1.0 MinMaxScaler() 0 -> 0.5495191298129259
281/3780 0.050 3.707 scale StandardScaler() 0 -> 0.5568100058677002
282/3780 0.050 3.707 scale MinMaxScaler() 0 -> 0.5518658990609243
283/3780 0.050 3.707 auto StandardScaler() 0 -> 0.556807916469538
284/3780 0.050 3.707 auto MinMaxScaler() 0 -> 0.5506912709734441
285/3780 0.050 3.707 0.01 StandardScaler() 0 -> 0.5505448506704497
286/3780 0.050 3.707 0.01 MinMaxScaler() 0 -> 0.5935194212706977
287/3780 0.050 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5485969033643437
288/3780 0.050 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5862013957052704
289/3780 0.050 3.707 0.1 StandardScaler() 0 -> 0.5489046212567481
290/3780 0.050 3.707 0.1 MinMaxScaler() 0 -> 0.5614603591079675
291/3780 0.050 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5679312961959098
292/3780 0.050 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5511623526705033
293/3780 0.050 3.707 1.0 StandardScaler() 0 -> 0.6238560803055196
294/3780 0.050 3.707 1.0 MinMaxScaler() 0 -> 0.5493752697632536
295/3780 0.050 4.703 scale StandardScaler() 0 -> 0.5592555570009808
296/3780 0.050 4.703 scale MinMaxScaler() 0 -> 0.5555697853103365
297/3780 0.050 4.703 auto StandardScaler() 0 -> 0.5592603597788691
298/3780 0.050 4.703 auto MinMaxScaler() 0 -> 0.5510332922132963
299/3780 0.050 4.703 0.01 StandardScaler() 0 -> 0.5505443569863627
300/3780 0.050 4.703 0.01 MinMaxScaler() 0 -> 0.5916737044128199
301/3780 0.050 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5485365717633924
302/3780 0.050 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5850851029263052
303/3780 0.050 4.703 0.1 StandardScaler() 0 -> 0.5495865947820892
304/3780 0.050 4.703 0.1 MinMaxScaler() 0 -> 0.5570431803175956
305/3780 0.050 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5738329322472687
306/3780 0.050 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5515549404276888
307/3780 0.050 4.703 1.0 StandardScaler() 0 -> 0.6391028445561284
308/3780 0.050 4.703 1.0 MinMaxScaler() 0 -> 0.5489470823258032
309/3780 0.050 5.968 scale StandardScaler() 0 -> 0.5626749432251662
310/3780 0.050 5.968 scale MinMaxScaler() 0 -> 0.5592451562194428
311/3780 0.050 5.968 auto StandardScaler() 0 -> 0.5626804191791552
312/3780 0.050 5.968 auto MinMaxScaler() 0 -> 0.5513749841848373
313/3780 0.050 5.968 0.01 StandardScaler() 0 -> 0.5509503286208688
314/3780 0.050 5.968 0.01 MinMaxScaler() 0 -> 0.5906278632866186
315/3780 0.050 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5484561142745318
316/3780 0.050 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5840987873815208
317/3780 0.050 5.968 0.1 StandardScaler() 0 -> 0.5506328346053039
318/3780 0.050 5.968 0.1 MinMaxScaler() 0 -> 0.5542179781398636
319/3780 0.050 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5781807418515933
320/3780 0.050 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5518692534439368
321/3780 0.050 5.968 1.0 StandardScaler() 0 -> 0.6584454695278948
322/3780 0.050 5.968 1.0 MinMaxScaler() 0 -> 0.5492997625311754
323/3780 0.050 7.574 scale StandardScaler() 0 -> 0.5678053264970006
324/3780 0.050 7.574 scale MinMaxScaler() 0 -> 0.5624179619615748
325/3780 0.050 7.574 auto StandardScaler() 0 -> 0.5678108214330684
326/3780 0.050 7.574 auto MinMaxScaler() 0 -> 0.5517022259423804
327/3780 0.050 7.574 0.01 StandardScaler() 0 -> 0.5508684069048878
328/3780 0.050 7.574 0.01 MinMaxScaler() 0 -> 0.589976534202516
329/3780 0.050 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5488824800281643
330/3780 0.050 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5824990110496936
331/3780 0.050 7.574 0.1 StandardScaler() 0 -> 0.5518963120524005
332/3780 0.050 7.574 0.1 MinMaxScaler() 0 -> 0.5523105803703272
333/3780 0.050 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5845891788320651
334/3780 0.050 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5518566880369343
335/3780 0.050 7.574 1.0 StandardScaler() 0 -> 0.6787531208416558
336/3780 0.050 7.574 1.0 MinMaxScaler() 0 -> 0.5493687775085455
337/3780 0.050 9.611 scale StandardScaler() 0 -> 0.5728953601456815
338/3780 0.050 9.611 scale MinMaxScaler() 0 -> 0.5662863081763111
339/3780 0.050 9.611 auto StandardScaler() 0 -> 0.5728947699800103
340/3780 0.050 9.611 auto MinMaxScaler() 0 -> 0.5521059884998364
341/3780 0.050 9.611 0.01 StandardScaler() 0 -> 0.5509382275081722
342/3780 0.050 9.611 0.01 MinMaxScaler() 0 -> 0.5898480404875633
343/3780 0.050 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5492368410578924
344/3780 0.050 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5803734407747556
345/3780 0.050 9.611 0.1 StandardScaler() 0 -> 0.553565063553335
346/3780 0.050 9.611 0.1 MinMaxScaler() 0 -> 0.5516396158537223
347/3780 0.050 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5929748467483917
348/3780 0.050 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5517382074131376
349/3780 0.050 9.611 1.0 StandardScaler() 0 -> 0.6987451446560723
350/3780 0.050 9.611 1.0 MinMaxScaler() 0 -> 0.549336372351607
351/3780 0.050 12.196 scale StandardScaler() 0 -> 0.5792773436508251
352/3780 0.050 12.196 scale MinMaxScaler() 0 -> 0.5716277917814085
353/3780 0.050 12.196 auto StandardScaler() 0 -> 0.5792801739300358
354/3780 0.050 12.196 auto MinMaxScaler() 0 -> 0.5528590884076682
355/3780 0.050 12.196 0.01 StandardScaler() 0 -> 0.5508290073142211
356/3780 0.050 12.196 0.01 MinMaxScaler() 0 -> 0.5894472476235415
357/3780 0.050 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5497286034778143
358/3780 0.050 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5778518758118344
359/3780 0.050 12.196 0.1 StandardScaler() 0 -> 0.5552242238358868
360/3780 0.050 12.196 0.1 MinMaxScaler() 0 -> 0.551447251007673
361/3780 0.050 12.196 0.31622776601683794 StandardScaler() 0 -> 0.6031048226272627
362/3780 0.050 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5514173533812453
363/3780 0.050 12.196 1.0 StandardScaler() 0 -> 0.7233036012738201
364/3780 0.050 12.196 1.0 MinMaxScaler() 0 -> 0.5492705330720901
365/3780 0.050 15.476 scale StandardScaler() 0 -> 0.5853736552393297
366/3780 0.050 15.476 scale MinMaxScaler() 0 -> 0.5777830998572068
367/3780 0.050 15.476 auto StandardScaler() 0 -> 0.5853762045372748
368/3780 0.050 15.476 auto MinMaxScaler() 0 -> 0.5530315366831038
369/3780 0.050 15.476 0.01 StandardScaler() 0 -> 0.5510194073626633
370/3780 0.050 15.476 0.01 MinMaxScaler() 0 -> 0.589165962048816
371/3780 0.050 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5503447783544549
372/3780 0.050 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5749289358795673
373/3780 0.050 15.476 0.1 StandardScaler() 0 -> 0.5579087092814111
374/3780 0.050 15.476 0.1 MinMaxScaler() 0 -> 0.5514308598298069
375/3780 0.050 15.476 0.31622776601683794 StandardScaler() 0 -> 0.6138134396711052
376/3780 0.050 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5515327706250378
377/3780 0.050 15.476 1.0 StandardScaler() 0 -> 0.7496044862943765
378/3780 0.050 15.476 1.0 MinMaxScaler() 0 -> 0.5490831120828628
379/3780 0.050 19.638 scale StandardScaler() 0 -> 0.593904748024081
380/3780 0.050 19.638 scale MinMaxScaler() 0 -> 0.5840115816998902
381/3780 0.050 19.638 auto StandardScaler() 0 -> 0.5939013115966522
382/3780 0.050 19.638 auto MinMaxScaler() 0 -> 0.5531037372808654
383/3780 0.050 19.638 0.01 StandardScaler() 0 -> 0.5509982051842699
384/3780 0.050 19.638 0.01 MinMaxScaler() 0 -> 0.5892791333321439
385/3780 0.050 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5505293305035545
386/3780 0.050 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5714353640170118
387/3780 0.050 19.638 0.1 StandardScaler() 0 -> 0.5602542806809897
388/3780 0.050 19.638 0.1 MinMaxScaler() 0 -> 0.5517051392593234
389/3780 0.050 19.638 0.31622776601683794 StandardScaler() 0 -> 0.6258095830364301
390/3780 0.050 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5514789838868235
391/3780 0.050 19.638 1.0 StandardScaler() 0 -> 0.7796167333687282
392/3780 0.050 19.638 1.0 MinMaxScaler() 0 -> 0.549246660722511
393/3780 0.050 24.920 scale StandardScaler() 0 -> 0.6029749356302379
394/3780 0.050 24.920 scale MinMaxScaler() 0 -> 0.5890298637791725
395/3780 0.050 24.920 auto StandardScaler() 0 -> 0.6029673978566928
396/3780 0.050 24.920 auto MinMaxScaler() 0 -> 0.553301984654956
397/3780 0.050 24.920 0.01 StandardScaler() 0 -> 0.5511644929544016
398/3780 0.050 24.920 0.01 MinMaxScaler() 0 -> 0.5887346289588989
399/3780 0.050 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5508340890709112
400/3780 0.050 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.568088723963737
401/3780 0.050 24.920 0.1 StandardScaler() 0 -> 0.5631121359618371
402/3780 0.050 24.920 0.1 MinMaxScaler() 0 -> 0.551900412972261
403/3780 0.050 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6405804253756336
404/3780 0.050 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5513010242312969
405/3780 0.050 24.920 1.0 StandardScaler() 0 -> 0.8151791718823836
406/3780 0.050 24.920 1.0 MinMaxScaler() 0 -> 0.5489521200159432
407/3780 0.050 31.623 scale StandardScaler() 0 -> 0.6099220910083915
408/3780 0.050 31.623 scale MinMaxScaler() 0 -> 0.5947370254705244
409/3780 0.050 31.623 auto StandardScaler() 0 -> 0.6099225201252482
410/3780 0.050 31.623 auto MinMaxScaler() 0 -> 0.5527830715300204
411/3780 0.050 31.623 0.01 StandardScaler() 0 -> 0.5512518679401602
412/3780 0.050 31.623 0.01 MinMaxScaler() 0 -> 0.5880621208028962
413/3780 0.050 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5510493355759044
414/3780 0.050 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5638717644916066
415/3780 0.050 31.623 0.1 StandardScaler() 0 -> 0.5656075411112065
416/3780 0.050 31.623 0.1 MinMaxScaler() 0 -> 0.552338019801275
417/3780 0.050 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6586201223311631
418/3780 0.050 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5515445770140893
419/3780 0.050 31.623 1.0 StandardScaler() 0 -> 0.8552735655514533
420/3780 0.050 31.623 1.0 MinMaxScaler() 0 -> 0.5494605001142817
421/3780 0.100 0.032 scale StandardScaler() 0 -> 0.5712277290168506
422/3780 0.100 0.032 scale MinMaxScaler() 0 -> 0.5666257830743092
423/3780 0.100 0.032 auto StandardScaler() 0 -> 0.5712277290168505
424/3780 0.100 0.032 auto MinMaxScaler() 0 -> 0.6561376352519098
425/3780 0.100 0.032 0.01 StandardScaler() 0 -> 0.6516246910812615
426/3780 0.100 0.032 0.01 MinMaxScaler() 0 -> 0.7425824094239554
427/3780 0.100 0.032 0.03162277660168379 StandardScaler() 0 -> 0.598869700172764
428/3780 0.100 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7166569802735641
429/3780 0.100 0.032 0.1 StandardScaler() 0 -> 0.5678084325447669
430/3780 0.100 0.032 0.1 MinMaxScaler() 0 -> 0.6811072141476466
431/3780 0.100 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5802943639304549
432/3780 0.100 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6372726808293194
433/3780 0.100 0.032 1.0 StandardScaler() 0 -> 0.6352619563891242
434/3780 0.100 0.032 1.0 MinMaxScaler() 0 -> 0.5859748469721904
435/3780 0.100 0.040 scale StandardScaler() 0 -> 0.5647419829322177
436/3780 0.100 0.040 scale MinMaxScaler() 0 -> 0.5608306497831975
437/3780 0.100 0.040 auto StandardScaler() 0 -> 0.5647419829322176
438/3780 0.100 0.040 auto MinMaxScaler() 0 -> 0.6458285690347721
439/3780 0.100 0.040 0.01 StandardScaler() 0 -> 0.6410533445954655
440/3780 0.100 0.040 0.01 MinMaxScaler() 0 -> 0.7390801393637988
441/3780 0.100 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5872616202535106
442/3780 0.100 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.707897661262772
443/3780 0.100 0.040 0.1 StandardScaler() 0 -> 0.560476822310092
444/3780 0.100 0.040 0.1 MinMaxScaler() 0 -> 0.6723470940403121
445/3780 0.100 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5730047817798102
446/3780 0.100 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.6263040818898414
447/3780 0.100 0.040 1.0 StandardScaler() 0 -> 0.6221735287238954
448/3780 0.100 0.040 1.0 MinMaxScaler() 0 -> 0.5771270049303147
449/3780 0.100 0.051 scale StandardScaler() 0 -> 0.5598975671010131
450/3780 0.100 0.051 scale MinMaxScaler() 0 -> 0.5570219256235358
451/3780 0.100 0.051 auto StandardScaler() 0 -> 0.5598975671010131
452/3780 0.100 0.051 auto MinMaxScaler() 0 -> 0.6352150195782054
453/3780 0.100 0.051 0.01 StandardScaler() 0 -> 0.6291989048604848
454/3780 0.100 0.051 0.01 MinMaxScaler() 0 -> 0.7347346136289642
455/3780 0.100 0.051 0.03162277660168379 StandardScaler() 0 -> 0.578968031959084
456/3780 0.100 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6999480234247039
457/3780 0.100 0.051 0.1 StandardScaler() 0 -> 0.5552857534821136
458/3780 0.100 0.051 0.1 MinMaxScaler() 0 -> 0.6636674122002924
459/3780 0.100 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5673823796846424
460/3780 0.100 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.6135615275975561
461/3780 0.100 0.051 1.0 StandardScaler() 0 -> 0.6105379224774855
462/3780 0.100 0.051 1.0 MinMaxScaler() 0 -> 0.5700274589956168
463/3780 0.100 0.065 scale StandardScaler() 0 -> 0.5567841013238579
464/3780 0.100 0.065 scale MinMaxScaler() 0 -> 0.5546616610469366
465/3780 0.100 0.065 auto StandardScaler() 0 -> 0.5567841013238578
466/3780 0.100 0.065 auto MinMaxScaler() 0 -> 0.6237818842416477
467/3780 0.100 0.065 0.01 StandardScaler() 0 -> 0.617879627929228
468/3780 0.100 0.065 0.01 MinMaxScaler() 0 -> 0.7293792734145851
469/3780 0.100 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5713336084982609
470/3780 0.100 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.693493811816825
471/3780 0.100 0.065 0.1 StandardScaler() 0 -> 0.5521052015219664
472/3780 0.100 0.065 0.1 MinMaxScaler() 0 -> 0.6540512395872978
473/3780 0.100 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5628803087682578
474/3780 0.100 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.6018739280231556
475/3780 0.100 0.065 1.0 StandardScaler() 0 -> 0.5992103248009079
476/3780 0.100 0.065 1.0 MinMaxScaler() 0 -> 0.5635944646100975
477/3780 0.100 0.082 scale StandardScaler() 0 -> 0.5547908098826643
478/3780 0.100 0.082 scale MinMaxScaler() 0 -> 0.5529196560728867
479/3780 0.100 0.082 auto StandardScaler() 0 -> 0.5547908098826642
480/3780 0.100 0.082 auto MinMaxScaler() 0 -> 0.6113107215350774
481/3780 0.100 0.082 0.01 StandardScaler() 0 -> 0.6058331720752878
482/3780 0.100 0.082 0.01 MinMaxScaler() 0 -> 0.7228395267714279
483/3780 0.100 0.082 0.03162277660168379 StandardScaler() 0 -> 0.564760009613284
484/3780 0.100 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6865625253092325
485/3780 0.100 0.082 0.1 StandardScaler() 0 -> 0.5507459540213411
486/3780 0.100 0.082 0.1 MinMaxScaler() 0 -> 0.6436068844805595
487/3780 0.100 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5588779142960889
488/3780 0.100 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5927778384642902
489/3780 0.100 0.082 1.0 StandardScaler() 0 -> 0.5885344117115475
490/3780 0.100 0.082 1.0 MinMaxScaler() 0 -> 0.5580802962056034
491/3780 0.100 0.104 scale StandardScaler() 0 -> 0.5526100788993249
492/3780 0.100 0.104 scale MinMaxScaler() 0 -> 0.551015887951701
493/3780 0.100 0.104 auto StandardScaler() 0 -> 0.5526100788993246
494/3780 0.100 0.104 auto MinMaxScaler() 0 -> 0.6008490482151446
495/3780 0.100 0.104 0.01 StandardScaler() 0 -> 0.5958946982859418
496/3780 0.100 0.104 0.01 MinMaxScaler() 0 -> 0.7149530240908
497/3780 0.100 0.104 0.03162277660168379 StandardScaler() 0 -> 0.559342602932542
498/3780 0.100 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6784957069602527
499/3780 0.100 0.104 0.1 StandardScaler() 0 -> 0.5490669139338548
500/3780 0.100 0.104 0.1 MinMaxScaler() 0 -> 0.6330484133023919
501/3780 0.100 0.104 0.31622776601683794 StandardScaler() 0 -> 0.555867580738987
502/3780 0.100 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5865782906843585
503/3780 0.100 0.104 1.0 StandardScaler() 0 -> 0.5789003230138218
504/3780 0.100 0.104 1.0 MinMaxScaler() 0 -> 0.5531745013339262
505/3780 0.100 0.132 scale StandardScaler() 0 -> 0.5507267310639243
506/3780 0.100 0.132 scale MinMaxScaler() 0 -> 0.5496165118212346
507/3780 0.100 0.132 auto StandardScaler() 0 -> 0.5507267310639242
508/3780 0.100 0.132 auto MinMaxScaler() 0 -> 0.5930502954664603
509/3780 0.100 0.132 0.01 StandardScaler() 0 -> 0.5890243086709204
510/3780 0.100 0.132 0.01 MinMaxScaler() 0 -> 0.7061216242274728
511/3780 0.100 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5540190242058142
512/3780 0.100 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6700324057190086
513/3780 0.100 0.132 0.1 StandardScaler() 0 -> 0.5479232624531069
514/3780 0.100 0.132 0.1 MinMaxScaler() 0 -> 0.6216428535503081
515/3780 0.100 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5532251624813803
516/3780 0.100 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5812628620105683
517/3780 0.100 0.132 1.0 StandardScaler() 0 -> 0.570094132036269
518/3780 0.100 0.132 1.0 MinMaxScaler() 0 -> 0.5498671778465805
519/3780 0.100 0.168 scale StandardScaler() 0 -> 0.5489228989618608
520/3780 0.100 0.168 scale MinMaxScaler() 0 -> 0.5480492045675275
521/3780 0.100 0.168 auto StandardScaler() 0 -> 0.5489228989618606
522/3780 0.100 0.168 auto MinMaxScaler() 0 -> 0.5875165849819481
523/3780 0.100 0.168 0.01 StandardScaler() 0 -> 0.5839926508808442
524/3780 0.100 0.168 0.01 MinMaxScaler() 0 -> 0.6985619647711862
525/3780 0.100 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5499122477182413
526/3780 0.100 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6616078932321972
527/3780 0.100 0.168 0.1 StandardScaler() 0 -> 0.5470793168607814
528/3780 0.100 0.168 0.1 MinMaxScaler() 0 -> 0.6097381971183432
529/3780 0.100 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5508305855823568
530/3780 0.100 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5772533589299226
531/3780 0.100 0.168 1.0 StandardScaler() 0 -> 0.562601333679175
532/3780 0.100 0.168 1.0 MinMaxScaler() 0 -> 0.5482648191042586
533/3780 0.100 0.213 scale StandardScaler() 0 -> 0.5477153667166031
534/3780 0.100 0.213 scale MinMaxScaler() 0 -> 0.5461506122133971
535/3780 0.100 0.213 auto StandardScaler() 0 -> 0.547715366716603
536/3780 0.100 0.213 auto MinMaxScaler() 0 -> 0.5840675058259657
537/3780 0.100 0.213 0.01 StandardScaler() 0 -> 0.5794029950201202
538/3780 0.100 0.213 0.01 MinMaxScaler() 0 -> 0.6919681172198883
539/3780 0.100 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5482183074574278
540/3780 0.100 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6515784060313551
541/3780 0.100 0.213 0.1 StandardScaler() 0 -> 0.5466876786593627
542/3780 0.100 0.213 0.1 MinMaxScaler() 0 -> 0.6000238746343302
543/3780 0.100 0.213 0.31622776601683794 StandardScaler() 0 -> 0.548592178951368
544/3780 0.100 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5730101988991902
545/3780 0.100 0.213 1.0 StandardScaler() 0 -> 0.556011751931889
546/3780 0.100 0.213 1.0 MinMaxScaler() 0 -> 0.5474342961385341
547/3780 0.100 0.270 scale StandardScaler() 0 -> 0.5465753704761608
548/3780 0.100 0.270 scale MinMaxScaler() 0 -> 0.5452083834897957
549/3780 0.100 0.270 auto StandardScaler() 0 -> 0.5465753704761607
550/3780 0.100 0.270 auto MinMaxScaler() 0 -> 0.5806082180479732
551/3780 0.100 0.270 0.01 StandardScaler() 0 -> 0.5752201271778757
552/3780 0.100 0.270 0.01 MinMaxScaler() 0 -> 0.6852249728677743
553/3780 0.100 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5475516889295439
554/3780 0.100 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6413590979740635
555/3780 0.100 0.270 0.1 StandardScaler() 0 -> 0.5464731459483628
556/3780 0.100 0.270 0.1 MinMaxScaler() 0 -> 0.5938527283435188
557/3780 0.100 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5461632621185684
558/3780 0.100 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.568815660765591
559/3780 0.100 0.270 1.0 StandardScaler() 0 -> 0.5506451446167113
560/3780 0.100 0.270 1.0 MinMaxScaler() 0 -> 0.546657111320759
561/3780 0.100 0.342 scale StandardScaler() 0 -> 0.5454943638693345
562/3780 0.100 0.342 scale MinMaxScaler() 0 -> 0.5441444022482825
563/3780 0.100 0.342 auto StandardScaler() 0 -> 0.5454943638710313
564/3780 0.100 0.342 auto MinMaxScaler() 0 -> 0.5773027893531554
565/3780 0.100 0.342 0.01 StandardScaler() 0 -> 0.5709305565151698
566/3780 0.100 0.342 0.01 MinMaxScaler() 0 -> 0.6769787818734696
567/3780 0.100 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5469265415148538
568/3780 0.100 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.6307303296522343
569/3780 0.100 0.342 0.1 StandardScaler() 0 -> 0.5465292025977057
570/3780 0.100 0.342 0.1 MinMaxScaler() 0 -> 0.5893501094935002
571/3780 0.100 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5447043299071382
572/3780 0.100 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5644401705418786
573/3780 0.100 0.342 1.0 StandardScaler() 0 -> 0.5474404216879515
574/3780 0.100 0.342 1.0 MinMaxScaler() 0 -> 0.5463517663896499
575/3780 0.100 0.434 scale StandardScaler() 0 -> 0.5446355523531037
576/3780 0.100 0.434 scale MinMaxScaler() 0 -> 0.5429083132729241
577/3780 0.100 0.434 auto StandardScaler() 0 -> 0.5446355523575735
578/3780 0.100 0.434 auto MinMaxScaler() 0 -> 0.5740021767942608
579/3780 0.100 0.434 0.01 StandardScaler() 0 -> 0.5662507711833921
580/3780 0.100 0.434 0.01 MinMaxScaler() 0 -> 0.6685386594865562
581/3780 0.100 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5463363192366947
582/3780 0.100 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.6188379851460923
583/3780 0.100 0.434 0.1 StandardScaler() 0 -> 0.5464558980214205
584/3780 0.100 0.434 0.1 MinMaxScaler() 0 -> 0.587052567582501
585/3780 0.100 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5437920348251473
586/3780 0.100 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5607142179685137
587/3780 0.100 0.434 1.0 StandardScaler() 0 -> 0.5461792919305307
588/3780 0.100 0.434 1.0 MinMaxScaler() 0 -> 0.5458938195845968
589/3780 0.100 0.551 scale StandardScaler() 0 -> 0.5436662384274092
590/3780 0.100 0.551 scale MinMaxScaler() 0 -> 0.5415273990602492
591/3780 0.100 0.551 auto StandardScaler() 0 -> 0.5436662384378486
592/3780 0.100 0.551 auto MinMaxScaler() 0 -> 0.5705735797158358
593/3780 0.100 0.551 0.01 StandardScaler() 0 -> 0.5620291387236572
594/3780 0.100 0.551 0.01 MinMaxScaler() 0 -> 0.6596293618573187
595/3780 0.100 0.551 0.03162277660168379 StandardScaler() 0 -> 0.54580552534856
596/3780 0.100 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.6084017442873942
597/3780 0.100 0.551 0.1 StandardScaler() 0 -> 0.5463590520105256
598/3780 0.100 0.551 0.1 MinMaxScaler() 0 -> 0.5849321611706424
599/3780 0.100 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5436243282039724
600/3780 0.100 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5563190070399441
601/3780 0.100 0.551 1.0 StandardScaler() 0 -> 0.5464247807203358
602/3780 0.100 0.551 1.0 MinMaxScaler() 0 -> 0.5456436034961426
603/3780 0.100 0.700 scale StandardScaler() 0 -> 0.5425924133363286
604/3780 0.100 0.700 scale MinMaxScaler() 0 -> 0.5410291800813953
605/3780 0.100 0.700 auto StandardScaler() 0 -> 0.5425958826992873
606/3780 0.100 0.700 auto MinMaxScaler() 0 -> 0.5668136554633274
607/3780 0.100 0.700 0.01 StandardScaler() 0 -> 0.5579905521146614
608/3780 0.100 0.700 0.01 MinMaxScaler() 0 -> 0.64934278222089
609/3780 0.100 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5456967387265467
610/3780 0.100 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5993114150651714
611/3780 0.100 0.700 0.1 StandardScaler() 0 -> 0.5463609278633169
612/3780 0.100 0.700 0.1 MinMaxScaler() 0 -> 0.5827866424437153
613/3780 0.100 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5434647721952129
614/3780 0.100 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5528234339888211
615/3780 0.100 0.700 1.0 StandardScaler() 0 -> 0.5488800403797559
616/3780 0.100 0.700 1.0 MinMaxScaler() 0 -> 0.5456827649509733
617/3780 0.100 0.888 scale StandardScaler() 0 -> 0.542838934290954
618/3780 0.100 0.888 scale MinMaxScaler() 0 -> 0.5411426063701893
619/3780 0.100 0.888 auto StandardScaler() 0 -> 0.5428389342791634
620/3780 0.100 0.888 auto MinMaxScaler() 0 -> 0.5630765008303128
621/3780 0.100 0.888 0.01 StandardScaler() 0 -> 0.554186791398885
622/3780 0.100 0.888 0.01 MinMaxScaler() 0 -> 0.6394320018549308
623/3780 0.100 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5453076155154742
624/3780 0.100 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.593795839500052
625/3780 0.100 0.888 0.1 StandardScaler() 0 -> 0.5459795408249963
626/3780 0.100 0.888 0.1 MinMaxScaler() 0 -> 0.5802518220170914
627/3780 0.100 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5444121726274498
628/3780 0.100 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5507281732751598
629/3780 0.100 0.888 1.0 StandardScaler() 0 -> 0.5534359615534931
630/3780 0.100 0.888 1.0 MinMaxScaler() 0 -> 0.545061739303703
631/3780 0.100 1.126 scale StandardScaler() 0 -> 0.5442191752136641
632/3780 0.100 1.126 scale MinMaxScaler() 0 -> 0.5417983535960863
633/3780 0.100 1.126 auto StandardScaler() 0 -> 0.5442191752136639
634/3780 0.100 1.126 auto MinMaxScaler() 0 -> 0.558593778428711
635/3780 0.100 1.126 0.01 StandardScaler() 0 -> 0.5515132770339367
636/3780 0.100 1.126 0.01 MinMaxScaler() 0 -> 0.6286107780744613
637/3780 0.100 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5451179894790595
638/3780 0.100 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5910925683549453
639/3780 0.100 1.126 0.1 StandardScaler() 0 -> 0.5456099089174802
640/3780 0.100 1.126 0.1 MinMaxScaler() 0 -> 0.5781573578041792
641/3780 0.100 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5460250932224416
642/3780 0.100 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5488542962017521
643/3780 0.100 1.126 1.0 StandardScaler() 0 -> 0.5595169313240529
644/3780 0.100 1.126 1.0 MinMaxScaler() 0 -> 0.545200584008644
645/3780 0.100 1.429 scale StandardScaler() 0 -> 0.5454024828785434
646/3780 0.100 1.429 scale MinMaxScaler() 0 -> 0.542616768876242
647/3780 0.100 1.429 auto StandardScaler() 0 -> 0.5454024828785426
648/3780 0.100 1.429 auto MinMaxScaler() 0 -> 0.55542420379409
649/3780 0.100 1.429 0.01 StandardScaler() 0 -> 0.5495704915803915
650/3780 0.100 1.429 0.01 MinMaxScaler() 0 -> 0.6166543956267855
651/3780 0.100 1.429 0.03162277660168379 StandardScaler() 0 -> 0.545309404581506
652/3780 0.100 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5892989188261677
653/3780 0.100 1.429 0.1 StandardScaler() 0 -> 0.5455099027775223
654/3780 0.100 1.429 0.1 MinMaxScaler() 0 -> 0.5755364511282388
655/3780 0.100 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5483097641825121
656/3780 0.100 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5482237039716978
657/3780 0.100 1.429 1.0 StandardScaler() 0 -> 0.5666862107036296
658/3780 0.100 1.429 1.0 MinMaxScaler() 0 -> 0.5452266527516006
659/3780 0.100 1.814 scale StandardScaler() 0 -> 0.5460817539808319
660/3780 0.100 1.814 scale MinMaxScaler() 0 -> 0.5436596853441734
661/3780 0.100 1.814 auto StandardScaler() 0 -> 0.5460817539808315
662/3780 0.100 1.814 auto MinMaxScaler() 0 -> 0.5520047205875003
663/3780 0.100 1.814 0.01 StandardScaler() 0 -> 0.5481682378991097
664/3780 0.100 1.814 0.01 MinMaxScaler() 0 -> 0.6067871299150792
665/3780 0.100 1.814 0.03162277660168379 StandardScaler() 0 -> 0.545434142893825
666/3780 0.100 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5884926842579182
667/3780 0.100 1.814 0.1 StandardScaler() 0 -> 0.5456746041462005
668/3780 0.100 1.814 0.1 MinMaxScaler() 0 -> 0.5726055788472598
669/3780 0.100 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5508132980212875
670/3780 0.100 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5477718084605764
671/3780 0.100 1.814 1.0 StandardScaler() 0 -> 0.5758397996180881
672/3780 0.100 1.814 1.0 MinMaxScaler() 0 -> 0.5453345227454326
673/3780 0.100 2.302 scale StandardScaler() 0 -> 0.5476764700242405
674/3780 0.100 2.302 scale MinMaxScaler() 0 -> 0.5456429128001593
675/3780 0.100 2.302 auto StandardScaler() 0 -> 0.5476764700242405
676/3780 0.100 2.302 auto MinMaxScaler() 0 -> 0.5504313724874185
677/3780 0.100 2.302 0.01 StandardScaler() 0 -> 0.5475162577009521
678/3780 0.100 2.302 0.01 MinMaxScaler() 0 -> 0.5986332559058077
679/3780 0.100 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5452916380298518
680/3780 0.100 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5879350495466898
681/3780 0.100 2.302 0.1 StandardScaler() 0 -> 0.5456419524611937
682/3780 0.100 2.302 0.1 MinMaxScaler() 0 -> 0.569008348416414
683/3780 0.100 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5549506787344937
684/3780 0.100 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5470660184545407
685/3780 0.100 2.302 1.0 StandardScaler() 0 -> 0.5878573578103803
686/3780 0.100 2.302 1.0 MinMaxScaler() 0 -> 0.5456649805869935
687/3780 0.100 2.921 scale StandardScaler() 0 -> 0.5498919404810212
688/3780 0.100 2.921 scale MinMaxScaler() 0 -> 0.5478557348580648
689/3780 0.100 2.921 auto StandardScaler() 0 -> 0.5498919404810199
690/3780 0.100 2.921 auto MinMaxScaler() 0 -> 0.5489974984166227
691/3780 0.100 2.921 0.01 StandardScaler() 0 -> 0.5473517737009496
692/3780 0.100 2.921 0.01 MinMaxScaler() 0 -> 0.5933194715458271
693/3780 0.100 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5461524564508713
694/3780 0.100 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.587290927459375
695/3780 0.100 2.921 0.1 StandardScaler() 0 -> 0.5453886774407539
696/3780 0.100 2.921 0.1 MinMaxScaler() 0 -> 0.5654034390900103
697/3780 0.100 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5591821096931849
698/3780 0.100 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5467674508429569
699/3780 0.100 2.921 1.0 StandardScaler() 0 -> 0.6012571618085657
700/3780 0.100 2.921 1.0 MinMaxScaler() 0 -> 0.5458238811312884
701/3780 0.100 3.707 scale StandardScaler() 0 -> 0.5522402284814611
702/3780 0.100 3.707 scale MinMaxScaler() 0 -> 0.5502821213419677
703/3780 0.100 3.707 auto StandardScaler() 0 -> 0.5522402284814633
704/3780 0.100 3.707 auto MinMaxScaler() 0 -> 0.5488085769526369
705/3780 0.100 3.707 0.01 StandardScaler() 0 -> 0.5469136428034521
706/3780 0.100 3.707 0.01 MinMaxScaler() 0 -> 0.5915902916023928
707/3780 0.100 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5458051581988254
708/3780 0.100 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5862595842411797
709/3780 0.100 3.707 0.1 StandardScaler() 0 -> 0.5455805407262398
710/3780 0.100 3.707 0.1 MinMaxScaler() 0 -> 0.5613248956606074
711/3780 0.100 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5639715098405383
712/3780 0.100 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5466595308321253
713/3780 0.100 3.707 1.0 StandardScaler() 0 -> 0.6135135293868856
714/3780 0.100 3.707 1.0 MinMaxScaler() 0 -> 0.5457356039706989
715/3780 0.100 4.703 scale StandardScaler() 0 -> 0.5552311486874438
716/3780 0.100 4.703 scale MinMaxScaler() 0 -> 0.5523414958873674
717/3780 0.100 4.703 auto StandardScaler() 0 -> 0.5552311486874423
718/3780 0.100 4.703 auto MinMaxScaler() 0 -> 0.5482146263014468
719/3780 0.100 4.703 0.01 StandardScaler() 0 -> 0.5470996050510588
720/3780 0.100 4.703 0.01 MinMaxScaler() 0 -> 0.5906718516336366
721/3780 0.100 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5463989833956425
722/3780 0.100 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5849960752799354
723/3780 0.100 4.703 0.1 StandardScaler() 0 -> 0.5459765244875103
724/3780 0.100 4.703 0.1 MinMaxScaler() 0 -> 0.5575733157074431
725/3780 0.100 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5691419801174002
726/3780 0.100 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5463329050731636
727/3780 0.100 4.703 1.0 StandardScaler() 0 -> 0.6276225071106581
728/3780 0.100 4.703 1.0 MinMaxScaler() 0 -> 0.545661044545198
729/3780 0.100 5.968 scale StandardScaler() 0 -> 0.5605855388847584
730/3780 0.100 5.968 scale MinMaxScaler() 0 -> 0.5548633372473896
731/3780 0.100 5.968 auto StandardScaler() 0 -> 0.5605855388847583
732/3780 0.100 5.968 auto MinMaxScaler() 0 -> 0.547445248716263
733/3780 0.100 5.968 0.01 StandardScaler() 0 -> 0.5469054613572712
734/3780 0.100 5.968 0.01 MinMaxScaler() 0 -> 0.589891757516116
735/3780 0.100 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5465211051227571
736/3780 0.100 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.583488863881286
737/3780 0.100 5.968 0.1 StandardScaler() 0 -> 0.5470070542131041
738/3780 0.100 5.968 0.1 MinMaxScaler() 0 -> 0.5542544151596176
739/3780 0.100 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5747816628483032
740/3780 0.100 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5463469256081486
741/3780 0.100 5.968 1.0 StandardScaler() 0 -> 0.6451774892503165
742/3780 0.100 5.968 1.0 MinMaxScaler() 0 -> 0.5461983473720958
743/3780 0.100 7.574 scale StandardScaler() 0 -> 0.5655027688788369
744/3780 0.100 7.574 scale MinMaxScaler() 0 -> 0.5585772046274206
745/3780 0.100 7.574 auto StandardScaler() 0 -> 0.5655027688788347
746/3780 0.100 7.574 auto MinMaxScaler() 0 -> 0.5475098909875183
747/3780 0.100 7.574 0.01 StandardScaler() 0 -> 0.5470390098329138
748/3780 0.100 7.574 0.01 MinMaxScaler() 0 -> 0.5898260689791552
749/3780 0.100 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5461401002891408
750/3780 0.100 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5815260337534833
751/3780 0.100 7.574 0.1 StandardScaler() 0 -> 0.5483894732346374
752/3780 0.100 7.574 0.1 MinMaxScaler() 0 -> 0.5520432015967724
753/3780 0.100 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5824940606328545
754/3780 0.100 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5463677656291224
755/3780 0.100 7.574 1.0 StandardScaler() 0 -> 0.6624286582584147
756/3780 0.100 7.574 1.0 MinMaxScaler() 0 -> 0.5462851215212544
757/3780 0.100 9.611 scale StandardScaler() 0 -> 0.5704073347081291
758/3780 0.100 9.611 scale MinMaxScaler() 0 -> 0.5626020840824203
759/3780 0.100 9.611 auto StandardScaler() 0 -> 0.570407334708123
760/3780 0.100 9.611 auto MinMaxScaler() 0 -> 0.547330683423744
761/3780 0.100 9.611 0.01 StandardScaler() 0 -> 0.5467975156117629
762/3780 0.100 9.611 0.01 MinMaxScaler() 0 -> 0.589638712536883
763/3780 0.100 9.611 0.03162277660168379 StandardScaler() 0 -> 0.546452001169626
764/3780 0.100 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5795949621691264
765/3780 0.100 9.611 0.1 StandardScaler() 0 -> 0.5497946120259205
766/3780 0.100 9.611 0.1 MinMaxScaler() 0 -> 0.5506231956010716
767/3780 0.100 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5914607989671988
768/3780 0.100 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5466632828658088
769/3780 0.100 9.611 1.0 StandardScaler() 0 -> 0.6815100731177632
770/3780 0.100 9.611 1.0 MinMaxScaler() 0 -> 0.5470092435924543
771/3780 0.100 12.196 scale StandardScaler() 0 -> 0.5757389423983706
772/3780 0.100 12.196 scale MinMaxScaler() 0 -> 0.5674293972537406
773/3780 0.100 12.196 auto StandardScaler() 0 -> 0.5757389423983695
774/3780 0.100 12.196 auto MinMaxScaler() 0 -> 0.5471954388785244
775/3780 0.100 12.196 0.01 StandardScaler() 0 -> 0.5470548281783273
776/3780 0.100 12.196 0.01 MinMaxScaler() 0 -> 0.5897385883397331
777/3780 0.100 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5467631363758544
778/3780 0.100 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5775255831725111
779/3780 0.100 12.196 0.1 StandardScaler() 0 -> 0.5522568433608785
780/3780 0.100 12.196 0.1 MinMaxScaler() 0 -> 0.5494027900970687
781/3780 0.100 12.196 0.31622776601683794 StandardScaler() 0 -> 0.6012302757635695
782/3780 0.100 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5469401227345217
783/3780 0.100 12.196 1.0 StandardScaler() 0 -> 0.7041682116915017
784/3780 0.100 12.196 1.0 MinMaxScaler() 0 -> 0.5471692963278606
785/3780 0.100 15.476 scale StandardScaler() 0 -> 0.5821478761870406
786/3780 0.100 15.476 scale MinMaxScaler() 0 -> 0.5731722949069247
787/3780 0.100 15.476 auto StandardScaler() 0 -> 0.5821478761870399
788/3780 0.100 15.476 auto MinMaxScaler() 0 -> 0.5472826813462479
789/3780 0.100 15.476 0.01 StandardScaler() 0 -> 0.5472086710818306
790/3780 0.100 15.476 0.01 MinMaxScaler() 0 -> 0.5893678858058901
791/3780 0.100 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5470100196690798
792/3780 0.100 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5743885802431193
793/3780 0.100 15.476 0.1 StandardScaler() 0 -> 0.5544512912017697
794/3780 0.100 15.476 0.1 MinMaxScaler() 0 -> 0.549292799747051
795/3780 0.100 15.476 0.31622776601683794 StandardScaler() 0 -> 0.6109892790597548
796/3780 0.100 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5467424375725266
797/3780 0.100 15.476 1.0 StandardScaler() 0 -> 0.727670303497416
798/3780 0.100 15.476 1.0 MinMaxScaler() 0 -> 0.547264922811758
799/3780 0.100 19.638 scale StandardScaler() 0 -> 0.5896785325155698
800/3780 0.100 19.638 scale MinMaxScaler() 0 -> 0.5790280664088775
801/3780 0.100 19.638 auto StandardScaler() 0 -> 0.5896785325155748
802/3780 0.100 19.638 auto MinMaxScaler() 0 -> 0.5474624832845115
803/3780 0.100 19.638 0.01 StandardScaler() 0 -> 0.5472202422942507
804/3780 0.100 19.638 0.01 MinMaxScaler() 0 -> 0.58895244816713
805/3780 0.100 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5474353968163357
806/3780 0.100 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5710553882305006
807/3780 0.100 19.638 0.1 StandardScaler() 0 -> 0.5565782824541792
808/3780 0.100 19.638 0.1 MinMaxScaler() 0 -> 0.5486027073665868
809/3780 0.100 19.638 0.31622776601683794 StandardScaler() 0 -> 0.6217757801540259
810/3780 0.100 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5463830424223305
811/3780 0.100 19.638 1.0 StandardScaler() 0 -> 0.7553547499814574
812/3780 0.100 19.638 1.0 MinMaxScaler() 0 -> 0.5473288628437426
813/3780 0.100 24.920 scale StandardScaler() 0 -> 0.5984667480108459
814/3780 0.100 24.920 scale MinMaxScaler() 0 -> 0.5845431832254815
815/3780 0.100 24.920 auto StandardScaler() 0 -> 0.5984728678305883
816/3780 0.100 24.920 auto MinMaxScaler() 0 -> 0.5473043951303377
817/3780 0.100 24.920 0.01 StandardScaler() 0 -> 0.5473352127868311
818/3780 0.100 24.920 0.01 MinMaxScaler() 0 -> 0.5881253282076252
819/3780 0.100 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5473301045242777
820/3780 0.100 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5673175855175855
821/3780 0.100 24.920 0.1 StandardScaler() 0 -> 0.5595331292179259
822/3780 0.100 24.920 0.1 MinMaxScaler() 0 -> 0.5481043992442493
823/3780 0.100 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6351330830618999
824/3780 0.100 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.547012172343086
825/3780 0.100 24.920 1.0 StandardScaler() 0 -> 0.7890694872386846
826/3780 0.100 24.920 1.0 MinMaxScaler() 0 -> 0.5473399436184256
827/3780 0.100 31.623 scale StandardScaler() 0 -> 0.6074196874494875
828/3780 0.100 31.623 scale MinMaxScaler() 0 -> 0.5900229288015783
829/3780 0.100 31.623 auto StandardScaler() 0 -> 0.6074196874494898
830/3780 0.100 31.623 auto MinMaxScaler() 0 -> 0.547651731719682
831/3780 0.100 31.623 0.01 StandardScaler() 0 -> 0.5473305921635695
832/3780 0.100 31.623 0.01 MinMaxScaler() 0 -> 0.5872208931269495
833/3780 0.100 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5479683232127665
834/3780 0.100 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5635744254325002
835/3780 0.100 31.623 0.1 StandardScaler() 0 -> 0.5619847363124661
836/3780 0.100 31.623 0.1 MinMaxScaler() 0 -> 0.5482993621872168
837/3780 0.100 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6500447736453102
838/3780 0.100 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5473281273494983
839/3780 0.100 31.623 1.0 StandardScaler() 0 -> 0.8247209026733358
840/3780 0.100 31.623 1.0 MinMaxScaler() 0 -> 0.5478095705736301
841/3780 0.150 0.032 scale StandardScaler() 0 -> 0.5658350539967549
842/3780 0.150 0.032 scale MinMaxScaler() 0 -> 0.5614297613102163
843/3780 0.150 0.032 auto StandardScaler() 0 -> 0.5658350539967548
844/3780 0.150 0.032 auto MinMaxScaler() 0 -> 0.6387008314560504
845/3780 0.150 0.032 0.01 StandardScaler() 0 -> 0.6346815398309668
846/3780 0.150 0.032 0.01 MinMaxScaler() 0 -> 0.7450137117296002
847/3780 0.150 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5880937290115078
848/3780 0.150 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7161899401198418
849/3780 0.150 0.032 0.1 StandardScaler() 0 -> 0.5632381486054289
850/3780 0.150 0.032 0.1 MinMaxScaler() 0 -> 0.6652842279751056
851/3780 0.150 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5741917264224462
852/3780 0.150 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6202297230815496
853/3780 0.150 0.032 1.0 StandardScaler() 0 -> 0.6271886781128054
854/3780 0.150 0.032 1.0 MinMaxScaler() 0 -> 0.5792437479009611
855/3780 0.150 0.040 scale StandardScaler() 0 -> 0.5599901077821382
856/3780 0.150 0.040 scale MinMaxScaler() 0 -> 0.5561129005856704
857/3780 0.150 0.040 auto StandardScaler() 0 -> 0.5599901077821382
858/3780 0.150 0.040 auto MinMaxScaler() 0 -> 0.6288730346220919
859/3780 0.150 0.040 0.01 StandardScaler() 0 -> 0.6239533176435481
860/3780 0.150 0.040 0.01 MinMaxScaler() 0 -> 0.7411459641022625
861/3780 0.150 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5809881404100622
862/3780 0.150 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7059959045213241
863/3780 0.150 0.040 0.1 StandardScaler() 0 -> 0.5566988391434787
864/3780 0.150 0.040 0.1 MinMaxScaler() 0 -> 0.6566554630296622
865/3780 0.150 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5674903028332285
866/3780 0.150 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.6096021605932114
867/3780 0.150 0.040 1.0 StandardScaler() 0 -> 0.6145773194510166
868/3780 0.150 0.040 1.0 MinMaxScaler() 0 -> 0.5724833981486132
869/3780 0.150 0.051 scale StandardScaler() 0 -> 0.5551114409153172
870/3780 0.150 0.051 scale MinMaxScaler() 0 -> 0.5530154070510248
871/3780 0.150 0.051 auto StandardScaler() 0 -> 0.555111440915317
872/3780 0.150 0.051 auto MinMaxScaler() 0 -> 0.618220779679585
873/3780 0.150 0.051 0.01 StandardScaler() 0 -> 0.6139028970714463
874/3780 0.150 0.051 0.01 MinMaxScaler() 0 -> 0.7363366615871426
875/3780 0.150 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5742250323053748
876/3780 0.150 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6941099981375
877/3780 0.150 0.051 0.1 StandardScaler() 0 -> 0.5529416912336566
878/3780 0.150 0.051 0.1 MinMaxScaler() 0 -> 0.6462231351069844
879/3780 0.150 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5626872081699591
880/3780 0.150 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.6005522531371983
881/3780 0.150 0.051 1.0 StandardScaler() 0 -> 0.6030180798897542
882/3780 0.150 0.051 1.0 MinMaxScaler() 0 -> 0.5659303435179383
883/3780 0.150 0.065 scale StandardScaler() 0 -> 0.5523421154510068
884/3780 0.150 0.065 scale MinMaxScaler() 0 -> 0.5503195571900709
885/3780 0.150 0.065 auto StandardScaler() 0 -> 0.5523421154510068
886/3780 0.150 0.065 auto MinMaxScaler() 0 -> 0.6081422749904166
887/3780 0.150 0.065 0.01 StandardScaler() 0 -> 0.6046171880707517
888/3780 0.150 0.065 0.01 MinMaxScaler() 0 -> 0.7303928067244053
889/3780 0.150 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5674646131031349
890/3780 0.150 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6814859660221048
891/3780 0.150 0.065 0.1 StandardScaler() 0 -> 0.54979900892629
892/3780 0.150 0.065 0.1 MinMaxScaler() 0 -> 0.6365452428352106
893/3780 0.150 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5581217693990571
894/3780 0.150 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5930286632221756
895/3780 0.150 0.065 1.0 StandardScaler() 0 -> 0.5924341882793133
896/3780 0.150 0.065 1.0 MinMaxScaler() 0 -> 0.5601906168566643
897/3780 0.150 0.082 scale StandardScaler() 0 -> 0.5498105092406095
898/3780 0.150 0.082 scale MinMaxScaler() 0 -> 0.5480339457302563
899/3780 0.150 0.082 auto StandardScaler() 0 -> 0.5498105092406094
900/3780 0.150 0.082 auto MinMaxScaler() 0 -> 0.6000239092663097
901/3780 0.150 0.082 0.01 StandardScaler() 0 -> 0.5959562049093634
902/3780 0.150 0.082 0.01 MinMaxScaler() 0 -> 0.7231062579426905
903/3780 0.150 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5617409158406912
904/3780 0.150 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.671552826734437
905/3780 0.150 0.082 0.1 StandardScaler() 0 -> 0.5478377006720646
906/3780 0.150 0.082 0.1 MinMaxScaler() 0 -> 0.6268148893723605
907/3780 0.150 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5537567493491206
908/3780 0.150 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.587195590745366
909/3780 0.150 0.082 1.0 StandardScaler() 0 -> 0.5821712429820688
910/3780 0.150 0.082 1.0 MinMaxScaler() 0 -> 0.5560352568487622
911/3780 0.150 0.104 scale StandardScaler() 0 -> 0.5477711910085215
912/3780 0.150 0.104 scale MinMaxScaler() 0 -> 0.5463177161548763
913/3780 0.150 0.104 auto StandardScaler() 0 -> 0.5477711910085213
914/3780 0.150 0.104 auto MinMaxScaler() 0 -> 0.5933983871131504
915/3780 0.150 0.104 0.01 StandardScaler() 0 -> 0.5897391092419507
916/3780 0.150 0.104 0.01 MinMaxScaler() 0 -> 0.7142706514508838
917/3780 0.150 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5568685846697482
918/3780 0.150 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6628153148195279
919/3780 0.150 0.104 0.1 StandardScaler() 0 -> 0.5458589952291998
920/3780 0.150 0.104 0.1 MinMaxScaler() 0 -> 0.616443603510594
921/3780 0.150 0.104 0.31622776601683794 StandardScaler() 0 -> 0.550769224387246
922/3780 0.150 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5830055083654617
923/3780 0.150 0.104 1.0 StandardScaler() 0 -> 0.5729204678593119
924/3780 0.150 0.104 1.0 MinMaxScaler() 0 -> 0.5518409956123341
925/3780 0.150 0.132 scale StandardScaler() 0 -> 0.5458057511336659
926/3780 0.150 0.132 scale MinMaxScaler() 0 -> 0.5446494100731445
927/3780 0.150 0.132 auto StandardScaler() 0 -> 0.5458057511336657
928/3780 0.150 0.132 auto MinMaxScaler() 0 -> 0.5879435276711761
929/3780 0.150 0.132 0.01 StandardScaler() 0 -> 0.5850881862345707
930/3780 0.150 0.132 0.01 MinMaxScaler() 0 -> 0.703722847094881
931/3780 0.150 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5527945744865924
932/3780 0.150 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6541602305487936
933/3780 0.150 0.132 0.1 StandardScaler() 0 -> 0.544824278578455
934/3780 0.150 0.132 0.1 MinMaxScaler() 0 -> 0.6070153547179095
935/3780 0.150 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5480631723276174
936/3780 0.150 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5788272640135131
937/3780 0.150 0.132 1.0 StandardScaler() 0 -> 0.5646367054712736
938/3780 0.150 0.132 1.0 MinMaxScaler() 0 -> 0.549741790652414
939/3780 0.150 0.168 scale StandardScaler() 0 -> 0.5442528148052862
940/3780 0.150 0.168 scale MinMaxScaler() 0 -> 0.5432753363293106
941/3780 0.150 0.168 auto StandardScaler() 0 -> 0.5442528148052861
942/3780 0.150 0.168 auto MinMaxScaler() 0 -> 0.5849410374974382
943/3780 0.150 0.168 0.01 StandardScaler() 0 -> 0.581370362995735
944/3780 0.150 0.168 0.01 MinMaxScaler() 0 -> 0.6915805557903223
945/3780 0.150 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5505153125067274
946/3780 0.150 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6440292710703542
947/3780 0.150 0.168 0.1 StandardScaler() 0 -> 0.5440934166316419
948/3780 0.150 0.168 0.1 MinMaxScaler() 0 -> 0.599863267192161
949/3780 0.150 0.168 0.31622776601683794 StandardScaler() 0 -> 0.545579755988888
950/3780 0.150 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5751015249680825
951/3780 0.150 0.168 1.0 StandardScaler() 0 -> 0.5577015564107065
952/3780 0.150 0.168 1.0 MinMaxScaler() 0 -> 0.5476782874928455
953/3780 0.150 0.213 scale StandardScaler() 0 -> 0.5432642172927477
954/3780 0.150 0.213 scale MinMaxScaler() 0 -> 0.5419120154261999
955/3780 0.150 0.213 auto StandardScaler() 0 -> 0.5432642172868415
956/3780 0.150 0.213 auto MinMaxScaler() 0 -> 0.5818018207485833
957/3780 0.150 0.213 0.01 StandardScaler() 0 -> 0.5771095303168376
958/3780 0.150 0.213 0.01 MinMaxScaler() 0 -> 0.6791747699782661
959/3780 0.150 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5488877355114342
960/3780 0.150 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6344519801742082
961/3780 0.150 0.213 0.1 StandardScaler() 0 -> 0.5433117987984646
962/3780 0.150 0.213 0.1 MinMaxScaler() 0 -> 0.5937805224977203
963/3780 0.150 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5437963529531998
964/3780 0.150 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5710220518686856
965/3780 0.150 0.213 1.0 StandardScaler() 0 -> 0.5519182911671421
966/3780 0.150 0.213 1.0 MinMaxScaler() 0 -> 0.5461515093656487
967/3780 0.150 0.270 scale StandardScaler() 0 -> 0.5422223005876946
968/3780 0.150 0.270 scale MinMaxScaler() 0 -> 0.5402436257679663
969/3780 0.150 0.270 auto StandardScaler() 0 -> 0.5422223005681089
970/3780 0.150 0.270 auto MinMaxScaler() 0 -> 0.5789560910362678
971/3780 0.150 0.270 0.01 StandardScaler() 0 -> 0.5732898105503895
972/3780 0.150 0.270 0.01 MinMaxScaler() 0 -> 0.669699596179954
973/3780 0.150 0.270 0.03162277660168379 StandardScaler() 0 -> 0.54702297072465
974/3780 0.150 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6243209958300534
975/3780 0.150 0.270 0.1 StandardScaler() 0 -> 0.5430815853066252
976/3780 0.150 0.270 0.1 MinMaxScaler() 0 -> 0.5894774101338613
977/3780 0.150 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5419139624658477
978/3780 0.150 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.567077581324162
979/3780 0.150 0.270 1.0 StandardScaler() 0 -> 0.5478692053433054
980/3780 0.150 0.270 1.0 MinMaxScaler() 0 -> 0.5450439286292235
981/3780 0.150 0.342 scale StandardScaler() 0 -> 0.5414645305080501
982/3780 0.150 0.342 scale MinMaxScaler() 0 -> 0.5390349537434017
983/3780 0.150 0.342 auto StandardScaler() 0 -> 0.5414645305080498
984/3780 0.150 0.342 auto MinMaxScaler() 0 -> 0.5757453342140807
985/3780 0.150 0.342 0.01 StandardScaler() 0 -> 0.5689940264298826
986/3780 0.150 0.342 0.01 MinMaxScaler() 0 -> 0.6610521092522011
987/3780 0.150 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5454755897774854
988/3780 0.150 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.6143490340189763
989/3780 0.150 0.342 0.1 StandardScaler() 0 -> 0.5429782165295246
990/3780 0.150 0.342 0.1 MinMaxScaler() 0 -> 0.5871774984919219
991/3780 0.150 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5403179376117225
992/3780 0.150 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5633029392376218
993/3780 0.150 0.342 1.0 StandardScaler() 0 -> 0.545255320693793
994/3780 0.150 0.342 1.0 MinMaxScaler() 0 -> 0.5444306098169972
995/3780 0.150 0.434 scale StandardScaler() 0 -> 0.5399380133648042
996/3780 0.150 0.434 scale MinMaxScaler() 0 -> 0.5381220773931958
997/3780 0.150 0.434 auto StandardScaler() 0 -> 0.5399380133648043
998/3780 0.150 0.434 auto MinMaxScaler() 0 -> 0.5727717407623681
999/3780 0.150 0.434 0.01 StandardScaler() 0 -> 0.5646768854894842
1000/3780 0.150 0.434 0.01 MinMaxScaler() 0 -> 0.6522420846665611
1001/3780 0.150 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5449062284069229
1002/3780 0.150 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.6059065757892106
1003/3780 0.150 0.434 0.1 StandardScaler() 0 -> 0.5426517723984053
1004/3780 0.150 0.434 0.1 MinMaxScaler() 0 -> 0.5852751885948347
1005/3780 0.150 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5395004245911061
1006/3780 0.150 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5590849556824099
1007/3780 0.150 0.434 1.0 StandardScaler() 0 -> 0.5440745711863845
1008/3780 0.150 0.434 1.0 MinMaxScaler() 0 -> 0.544089338504974
1009/3780 0.150 0.551 scale StandardScaler() 0 -> 0.5396744405942735
1010/3780 0.150 0.551 scale MinMaxScaler() 0 -> 0.5370137072135527
1011/3780 0.150 0.551 auto StandardScaler() 0 -> 0.5396744405942732
1012/3780 0.150 0.551 auto MinMaxScaler() 0 -> 0.5694520080852027
1013/3780 0.150 0.551 0.01 StandardScaler() 0 -> 0.5600043044191705
1014/3780 0.150 0.551 0.01 MinMaxScaler() 0 -> 0.6421655699600538
1015/3780 0.150 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5443485524764005
1016/3780 0.150 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5994834946657769
1017/3780 0.150 0.551 0.1 StandardScaler() 0 -> 0.5418510476135224
1018/3780 0.150 0.551 0.1 MinMaxScaler() 0 -> 0.5832539146138312
1019/3780 0.150 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5391669623822333
1020/3780 0.150 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5556361212524182
1021/3780 0.150 0.551 1.0 StandardScaler() 0 -> 0.5447357338707653
1022/3780 0.150 0.551 1.0 MinMaxScaler() 0 -> 0.5436635615118158
1023/3780 0.150 0.700 scale StandardScaler() 0 -> 0.5399532484022863
1024/3780 0.150 0.700 scale MinMaxScaler() 0 -> 0.5368030087792234
1025/3780 0.150 0.700 auto StandardScaler() 0 -> 0.5399532484022859
1026/3780 0.150 0.700 auto MinMaxScaler() 0 -> 0.5654783886238026
1027/3780 0.150 0.700 0.01 StandardScaler() 0 -> 0.5558523734433644
1028/3780 0.150 0.700 0.01 MinMaxScaler() 0 -> 0.6323286408399797
1029/3780 0.150 0.700 0.03162277660168379 StandardScaler() 0 -> 0.543733362411575
1030/3780 0.150 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5940132892631271
1031/3780 0.150 0.700 0.1 StandardScaler() 0 -> 0.5414150438717039
1032/3780 0.150 0.700 0.1 MinMaxScaler() 0 -> 0.5812340373269264
1033/3780 0.150 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5395214415359214
1034/3780 0.150 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5525846091275005
1035/3780 0.150 0.700 1.0 StandardScaler() 0 -> 0.5465872191695301
1036/3780 0.150 0.700 1.0 MinMaxScaler() 0 -> 0.5432767224459386
1037/3780 0.150 0.888 scale StandardScaler() 0 -> 0.540293117207243
1038/3780 0.150 0.888 scale MinMaxScaler() 0 -> 0.5371500785553044
1039/3780 0.150 0.888 auto StandardScaler() 0 -> 0.540293117207243
1040/3780 0.150 0.888 auto MinMaxScaler() 0 -> 0.5618505257198357
1041/3780 0.150 0.888 0.01 StandardScaler() 0 -> 0.5535316690030933
1042/3780 0.150 0.888 0.01 MinMaxScaler() 0 -> 0.6225138991140368
1043/3780 0.150 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5434637753810594
1044/3780 0.150 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5908370062766696
1045/3780 0.150 0.888 0.1 StandardScaler() 0 -> 0.5404442994609266
1046/3780 0.150 0.888 0.1 MinMaxScaler() 0 -> 0.5792186280231195
1047/3780 0.150 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5402400576682228
1048/3780 0.150 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5506366674501221
1049/3780 0.150 0.888 1.0 StandardScaler() 0 -> 0.5516743014085134
1050/3780 0.150 0.888 1.0 MinMaxScaler() 0 -> 0.5428132169242803
1051/3780 0.150 1.126 scale StandardScaler() 0 -> 0.5404351251516064
1052/3780 0.150 1.126 scale MinMaxScaler() 0 -> 0.5380321898979061
1053/3780 0.150 1.126 auto StandardScaler() 0 -> 0.540435125151606
1054/3780 0.150 1.126 auto MinMaxScaler() 0 -> 0.5582674196791714
1055/3780 0.150 1.126 0.01 StandardScaler() 0 -> 0.5517596459250464
1056/3780 0.150 1.126 0.01 MinMaxScaler() 0 -> 0.6129751710201176
1057/3780 0.150 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5435305622781164
1058/3780 0.150 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5892631693308515
1059/3780 0.150 1.126 0.1 StandardScaler() 0 -> 0.5404111370552892
1060/3780 0.150 1.126 0.1 MinMaxScaler() 0 -> 0.5772140741614264
1061/3780 0.150 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5419750670396358
1062/3780 0.150 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.54843039217418
1063/3780 0.150 1.126 1.0 StandardScaler() 0 -> 0.5565545499745251
1064/3780 0.150 1.126 1.0 MinMaxScaler() 0 -> 0.5425480260511124
1065/3780 0.150 1.429 scale StandardScaler() 0 -> 0.5415700308264907
1066/3780 0.150 1.429 scale MinMaxScaler() 0 -> 0.5385692952578227
1067/3780 0.150 1.429 auto StandardScaler() 0 -> 0.5415700308264904
1068/3780 0.150 1.429 auto MinMaxScaler() 0 -> 0.5546261931343454
1069/3780 0.150 1.429 0.01 StandardScaler() 0 -> 0.5495356740188101
1070/3780 0.150 1.429 0.01 MinMaxScaler() 0 -> 0.604816549600827
1071/3780 0.150 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5435772947291578
1072/3780 0.150 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5881063786775794
1073/3780 0.150 1.429 0.1 StandardScaler() 0 -> 0.540606479218318
1074/3780 0.150 1.429 0.1 MinMaxScaler() 0 -> 0.5744815069569938
1075/3780 0.150 1.429 0.31622776601683794 StandardScaler() 0 -> 0.543847777517172
1076/3780 0.150 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.547271361821481
1077/3780 0.150 1.429 1.0 StandardScaler() 0 -> 0.5630980687427231
1078/3780 0.150 1.429 1.0 MinMaxScaler() 0 -> 0.5428538166560698
1079/3780 0.150 1.814 scale StandardScaler() 0 -> 0.5430131810984328
1080/3780 0.150 1.814 scale MinMaxScaler() 0 -> 0.5401426600068141
1081/3780 0.150 1.814 auto StandardScaler() 0 -> 0.5430131810984334
1082/3780 0.150 1.814 auto MinMaxScaler() 0 -> 0.5519181885332466
1083/3780 0.150 1.814 0.01 StandardScaler() 0 -> 0.5480678532661006
1084/3780 0.150 1.814 0.01 MinMaxScaler() 0 -> 0.5986578223409309
1085/3780 0.150 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5431192728696161
1086/3780 0.150 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5873000393608115
1087/3780 0.150 1.814 0.1 StandardScaler() 0 -> 0.5408195999429442
1088/3780 0.150 1.814 0.1 MinMaxScaler() 0 -> 0.5715459100792127
1089/3780 0.150 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5476399018975538
1090/3780 0.150 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5461310615614168
1091/3780 0.150 1.814 1.0 StandardScaler() 0 -> 0.5723285496867151
1092/3780 0.150 1.814 1.0 MinMaxScaler() 0 -> 0.5428267870914881
1093/3780 0.150 2.302 scale StandardScaler() 0 -> 0.544601387285731
1094/3780 0.150 2.302 scale MinMaxScaler() 0 -> 0.5421902263202022
1095/3780 0.150 2.302 auto StandardScaler() 0 -> 0.5446013872857304
1096/3780 0.150 2.302 auto MinMaxScaler() 0 -> 0.5506335778750261
1097/3780 0.150 2.302 0.01 StandardScaler() 0 -> 0.5468812459463201
1098/3780 0.150 2.302 0.01 MinMaxScaler() 0 -> 0.5937521737248191
1099/3780 0.150 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5434236622263896
1100/3780 0.150 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5863556443307987
1101/3780 0.150 2.302 0.1 StandardScaler() 0 -> 0.5414609956658817
1102/3780 0.150 2.302 0.1 MinMaxScaler() 0 -> 0.5683778422571527
1103/3780 0.150 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5514446525664667
1104/3780 0.150 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5455869052106976
1105/3780 0.150 2.302 1.0 StandardScaler() 0 -> 0.5827548527625844
1106/3780 0.150 2.302 1.0 MinMaxScaler() 0 -> 0.5430275900030507
1107/3780 0.150 2.921 scale StandardScaler() 0 -> 0.5463079804418302
1108/3780 0.150 2.921 scale MinMaxScaler() 0 -> 0.5442597792768996
1109/3780 0.150 2.921 auto StandardScaler() 0 -> 0.5463079804418288
1110/3780 0.150 2.921 auto MinMaxScaler() 0 -> 0.5487033777017724
1111/3780 0.150 2.921 0.01 StandardScaler() 0 -> 0.5459906251690841
1112/3780 0.150 2.921 0.01 MinMaxScaler() 0 -> 0.5912835732361686
1113/3780 0.150 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5430956838127691
1114/3780 0.150 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5856120302234077
1115/3780 0.150 2.921 0.1 StandardScaler() 0 -> 0.5413147885779378
1116/3780 0.150 2.921 0.1 MinMaxScaler() 0 -> 0.5643792226906027
1117/3780 0.150 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5555947740161679
1118/3780 0.150 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5452835808971037
1119/3780 0.150 2.921 1.0 StandardScaler() 0 -> 0.5936107849326554
1120/3780 0.150 2.921 1.0 MinMaxScaler() 0 -> 0.5429980768250897
1121/3780 0.150 3.707 scale StandardScaler() 0 -> 0.5487296263090379
1122/3780 0.150 3.707 scale MinMaxScaler() 0 -> 0.5461627460267028
1123/3780 0.150 3.707 auto StandardScaler() 0 -> 0.5487296263090391
1124/3780 0.150 3.707 auto MinMaxScaler() 0 -> 0.5476220729478314
1125/3780 0.150 3.707 0.01 StandardScaler() 0 -> 0.5455759255230561
1126/3780 0.150 3.707 0.01 MinMaxScaler() 0 -> 0.5897798186447388
1127/3780 0.150 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5430570794760404
1128/3780 0.150 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5849754194196185
1129/3780 0.150 3.707 0.1 StandardScaler() 0 -> 0.5414999469351375
1130/3780 0.150 3.707 0.1 MinMaxScaler() 0 -> 0.5611837562319485
1131/3780 0.150 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5604589054914109
1132/3780 0.150 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5454279777569835
1133/3780 0.150 3.707 1.0 StandardScaler() 0 -> 0.6048179350747599
1134/3780 0.150 3.707 1.0 MinMaxScaler() 0 -> 0.5432017955433244
1135/3780 0.150 4.703 scale StandardScaler() 0 -> 0.5517659870148878
1136/3780 0.150 4.703 scale MinMaxScaler() 0 -> 0.5489222237471606
1137/3780 0.150 4.703 auto StandardScaler() 0 -> 0.5517659870148862
1138/3780 0.150 4.703 auto MinMaxScaler() 0 -> 0.5465269323685965
1139/3780 0.150 4.703 0.01 StandardScaler() 0 -> 0.5455058491139774
1140/3780 0.150 4.703 0.01 MinMaxScaler() 0 -> 0.5891388964839361
1141/3780 0.150 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5434357108423136
1142/3780 0.150 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5839900365027275
1143/3780 0.150 4.703 0.1 StandardScaler() 0 -> 0.5422814479305463
1144/3780 0.150 4.703 0.1 MinMaxScaler() 0 -> 0.557064236420846
1145/3780 0.150 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5661688896069631
1146/3780 0.150 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5450354081191325
1147/3780 0.150 4.703 1.0 StandardScaler() 0 -> 0.6173329948008459
1148/3780 0.150 4.703 1.0 MinMaxScaler() 0 -> 0.5433500555441593
1149/3780 0.150 5.968 scale StandardScaler() 0 -> 0.5565878270851349
1150/3780 0.150 5.968 scale MinMaxScaler() 0 -> 0.5525824300020657
1151/3780 0.150 5.968 auto StandardScaler() 0 -> 0.5565878270851349
1152/3780 0.150 5.968 auto MinMaxScaler() 0 -> 0.5460417765563627
1153/3780 0.150 5.968 0.01 StandardScaler() 0 -> 0.5453819972743891
1154/3780 0.150 5.968 0.01 MinMaxScaler() 0 -> 0.5883988259932716
1155/3780 0.150 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5429360414438881
1156/3780 0.150 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5826122215221603
1157/3780 0.150 5.968 0.1 StandardScaler() 0 -> 0.5443538445843802
1158/3780 0.150 5.968 0.1 MinMaxScaler() 0 -> 0.554049944161118
1159/3780 0.150 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5732360248041263
1160/3780 0.150 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5446984272997298
1161/3780 0.150 5.968 1.0 StandardScaler() 0 -> 0.6315447365734984
1162/3780 0.150 5.968 1.0 MinMaxScaler() 0 -> 0.5430844613521382
1163/3780 0.150 7.574 scale StandardScaler() 0 -> 0.5607964746213111
1164/3780 0.150 7.574 scale MinMaxScaler() 0 -> 0.5555298225570994
1165/3780 0.150 7.574 auto StandardScaler() 0 -> 0.5607964746213092
1166/3780 0.150 7.574 auto MinMaxScaler() 0 -> 0.5459747697152438
1167/3780 0.150 7.574 0.01 StandardScaler() 0 -> 0.5453181134740285
1168/3780 0.150 7.574 0.01 MinMaxScaler() 0 -> 0.5880914827526353
1169/3780 0.150 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5428094308098039
1170/3780 0.150 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5810283403907207
1171/3780 0.150 7.574 0.1 StandardScaler() 0 -> 0.5460723237122989
1172/3780 0.150 7.574 0.1 MinMaxScaler() 0 -> 0.5519208285828943
1173/3780 0.150 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5808259001096431
1174/3780 0.150 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5444153404824049
1175/3780 0.150 7.574 1.0 StandardScaler() 0 -> 0.6472368547049606
1176/3780 0.150 7.574 1.0 MinMaxScaler() 0 -> 0.542847820049379
1177/3780 0.150 9.611 scale StandardScaler() 0 -> 0.5653832120132446
1178/3780 0.150 9.611 scale MinMaxScaler() 0 -> 0.5596285434740276
1179/3780 0.150 9.611 auto StandardScaler() 0 -> 0.5653832120132357
1180/3780 0.150 9.611 auto MinMaxScaler() 0 -> 0.5459614929009013
1181/3780 0.150 9.611 0.01 StandardScaler() 0 -> 0.5452097280059566
1182/3780 0.150 9.611 0.01 MinMaxScaler() 0 -> 0.5879578029775927
1183/3780 0.150 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5425814117588367
1184/3780 0.150 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5790438684837977
1185/3780 0.150 9.611 0.1 StandardScaler() 0 -> 0.5470374167447974
1186/3780 0.150 9.611 0.1 MinMaxScaler() 0 -> 0.5502572905320439
1187/3780 0.150 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5884549806586958
1188/3780 0.150 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5444168621294996
1189/3780 0.150 9.611 1.0 StandardScaler() 0 -> 0.665632763329071
1190/3780 0.150 9.611 1.0 MinMaxScaler() 0 -> 0.542851858211795
1191/3780 0.150 12.196 scale StandardScaler() 0 -> 0.5712761791032722
1192/3780 0.150 12.196 scale MinMaxScaler() 0 -> 0.563985121277515
1193/3780 0.150 12.196 auto StandardScaler() 0 -> 0.5712761791032741
1194/3780 0.150 12.196 auto MinMaxScaler() 0 -> 0.5456392776225415
1195/3780 0.150 12.196 0.01 StandardScaler() 0 -> 0.5452104319946088
1196/3780 0.150 12.196 0.01 MinMaxScaler() 0 -> 0.5879479413274277
1197/3780 0.150 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5425275342646417
1198/3780 0.150 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5767303228589323
1199/3780 0.150 12.196 0.1 StandardScaler() 0 -> 0.5490670722515406
1200/3780 0.150 12.196 0.1 MinMaxScaler() 0 -> 0.548856288467099
1201/3780 0.150 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5964266076591214
1202/3780 0.150 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5441659921270072
1203/3780 0.150 12.196 1.0 StandardScaler() 0 -> 0.6865294679654589
1204/3780 0.150 12.196 1.0 MinMaxScaler() 0 -> 0.5430990367987009
1205/3780 0.150 15.476 scale StandardScaler() 0 -> 0.5770076231493045
1206/3780 0.150 15.476 scale MinMaxScaler() 0 -> 0.5688231269167237
1207/3780 0.150 15.476 auto StandardScaler() 0 -> 0.5770076231493045
1208/3780 0.150 15.476 auto MinMaxScaler() 0 -> 0.5454474973436008
1209/3780 0.150 15.476 0.01 StandardScaler() 0 -> 0.5452794542436877
1210/3780 0.150 15.476 0.01 MinMaxScaler() 0 -> 0.5878516212078676
1211/3780 0.150 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5425546600837532
1212/3780 0.150 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5740861013714024
1213/3780 0.150 15.476 0.1 StandardScaler() 0 -> 0.5511633977018993
1214/3780 0.150 15.476 0.1 MinMaxScaler() 0 -> 0.5480963202065127
1215/3780 0.150 15.476 0.31622776601683794 StandardScaler() 0 -> 0.6057549930767403
1216/3780 0.150 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5442758221139786
1217/3780 0.150 15.476 1.0 StandardScaler() 0 -> 0.7087694886128629
1218/3780 0.150 15.476 1.0 MinMaxScaler() 0 -> 0.5426036748766984
1219/3780 0.150 19.638 scale StandardScaler() 0 -> 0.5850629239073402
1220/3780 0.150 19.638 scale MinMaxScaler() 0 -> 0.5734081219634012
1221/3780 0.150 19.638 auto StandardScaler() 0 -> 0.5850629239073447
1222/3780 0.150 19.638 auto MinMaxScaler() 0 -> 0.5453444289927617
1223/3780 0.150 19.638 0.01 StandardScaler() 0 -> 0.5449941750386127
1224/3780 0.150 19.638 0.01 MinMaxScaler() 0 -> 0.587515811681921
1225/3780 0.150 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5426562660782405
1226/3780 0.150 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5708079920568184
1227/3780 0.150 19.638 0.1 StandardScaler() 0 -> 0.5531938776478849
1228/3780 0.150 19.638 0.1 MinMaxScaler() 0 -> 0.5468893364701972
1229/3780 0.150 19.638 0.31622776601683794 StandardScaler() 0 -> 0.6163579010668264
1230/3780 0.150 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.544115350293739
1231/3780 0.150 19.638 1.0 StandardScaler() 0 -> 0.7357299692998037
1232/3780 0.150 19.638 1.0 MinMaxScaler() 0 -> 0.5421813066229029
1233/3780 0.150 24.920 scale StandardScaler() 0 -> 0.5929445583197017
1234/3780 0.150 24.920 scale MinMaxScaler() 0 -> 0.5787832200260502
1235/3780 0.150 24.920 auto StandardScaler() 0 -> 0.5929445583196996
1236/3780 0.150 24.920 auto MinMaxScaler() 0 -> 0.545260301727177
1237/3780 0.150 24.920 0.01 StandardScaler() 0 -> 0.5445541100976526
1238/3780 0.150 24.920 0.01 MinMaxScaler() 0 -> 0.5871783441409237
1239/3780 0.150 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5424971644701143
1240/3780 0.150 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5671494679363714
1241/3780 0.150 24.920 0.1 StandardScaler() 0 -> 0.5559591994939671
1242/3780 0.150 24.920 0.1 MinMaxScaler() 0 -> 0.5467412501027232
1243/3780 0.150 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6297291312470642
1244/3780 0.150 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5439000612094361
1245/3780 0.150 24.920 1.0 StandardScaler() 0 -> 0.7669490024330919
1246/3780 0.150 24.920 1.0 MinMaxScaler() 0 -> 0.5423445560649349
1247/3780 0.150 31.623 scale StandardScaler() 0 -> 0.6039126463386152
1248/3780 0.150 31.623 scale MinMaxScaler() 0 -> 0.5833850353725455
1249/3780 0.150 31.623 auto StandardScaler() 0 -> 0.603912646338627
1250/3780 0.150 31.623 auto MinMaxScaler() 0 -> 0.5452100962191334
1251/3780 0.150 31.623 0.01 StandardScaler() 0 -> 0.5444404236643424
1252/3780 0.150 31.623 0.01 MinMaxScaler() 0 -> 0.586338718079864
1253/3780 0.150 31.623 0.03162277660168379 StandardScaler() 0 -> 0.543177315454534
1254/3780 0.150 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5636466967030878
1255/3780 0.150 31.623 0.1 StandardScaler() 0 -> 0.5583558059398981
1256/3780 0.150 31.623 0.1 MinMaxScaler() 0 -> 0.5463593434091151
1257/3780 0.150 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6459051418869562
1258/3780 0.150 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5440939421673205
1259/3780 0.150 31.623 1.0 StandardScaler() 0 -> 0.800131085501614
1260/3780 0.150 31.623 1.0 MinMaxScaler() 0 -> 0.5425008853654553
1261/3780 0.200 0.032 scale StandardScaler() 0 -> 0.5622653197354835
1262/3780 0.200 0.032 scale MinMaxScaler() 0 -> 0.5585672200439152
1263/3780 0.200 0.032 auto StandardScaler() 0 -> 0.5622653197354835
1264/3780 0.200 0.032 auto MinMaxScaler() 0 -> 0.6265238411171098
1265/3780 0.200 0.032 0.01 StandardScaler() 0 -> 0.6222374486875878
1266/3780 0.200 0.032 0.01 MinMaxScaler() 0 -> 0.7524450140352453
1267/3780 0.200 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5825495867260205
1268/3780 0.200 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7207228999661192
1269/3780 0.200 0.032 0.1 StandardScaler() 0 -> 0.5595398898964513
1270/3780 0.200 0.032 0.1 MinMaxScaler() 0 -> 0.6539549309955975
1271/3780 0.200 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5696165947649555
1272/3780 0.200 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6088839648920472
1273/3780 0.200 0.032 1.0 StandardScaler() 0 -> 0.6231445710509537
1274/3780 0.200 0.032 1.0 MinMaxScaler() 0 -> 0.5747947729303794
1275/3780 0.200 0.040 scale StandardScaler() 0 -> 0.5574250218332876
1276/3780 0.200 0.040 scale MinMaxScaler() 0 -> 0.5540648132846713
1277/3780 0.200 0.040 auto StandardScaler() 0 -> 0.5574250218332875
1278/3780 0.200 0.040 auto MinMaxScaler() 0 -> 0.6163797520808918
1279/3780 0.200 0.040 0.01 StandardScaler() 0 -> 0.6123583996338121
1280/3780 0.200 0.040 0.01 MinMaxScaler() 0 -> 0.7482117888407264
1281/3780 0.200 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5761738060268653
1282/3780 0.200 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.709383845705025
1283/3780 0.200 0.040 0.1 StandardScaler() 0 -> 0.5552058212669403
1284/3780 0.200 0.040 0.1 MinMaxScaler() 0 -> 0.6437765369053389
1285/3780 0.200 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5634795462256167
1286/3780 0.200 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5998677893975805
1287/3780 0.200 0.040 1.0 StandardScaler() 0 -> 0.6101930365895906
1288/3780 0.200 0.040 1.0 MinMaxScaler() 0 -> 0.568751953759331
1289/3780 0.200 0.051 scale StandardScaler() 0 -> 0.5533867547381042
1290/3780 0.200 0.051 scale MinMaxScaler() 0 -> 0.550580345849322
1291/3780 0.200 0.051 auto StandardScaler() 0 -> 0.5533867547381041
1292/3780 0.200 0.051 auto MinMaxScaler() 0 -> 0.6070993084013286
1293/3780 0.200 0.051 0.01 StandardScaler() 0 -> 0.6037277804457252
1294/3780 0.200 0.051 0.01 MinMaxScaler() 0 -> 0.7429387095453205
1295/3780 0.200 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5704476201534417
1296/3780 0.200 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.695933782637522
1297/3780 0.200 0.051 0.1 StandardScaler() 0 -> 0.5517356971909604
1298/3780 0.200 0.051 0.1 MinMaxScaler() 0 -> 0.6345503230927038
1299/3780 0.200 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5588272971470083
1300/3780 0.200 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5925679066194516
1301/3780 0.200 0.051 1.0 StandardScaler() 0 -> 0.5984692971626112
1302/3780 0.200 0.051 1.0 MinMaxScaler() 0 -> 0.5636906196468418
1303/3780 0.200 0.065 scale StandardScaler() 0 -> 0.550482333881496
1304/3780 0.200 0.065 scale MinMaxScaler() 0 -> 0.5481144491110554
1305/3780 0.200 0.065 auto StandardScaler() 0 -> 0.550482333881496
1306/3780 0.200 0.065 auto MinMaxScaler() 0 -> 0.5989970208303909
1307/3780 0.200 0.065 0.01 StandardScaler() 0 -> 0.5961538415542064
1308/3780 0.200 0.065 0.01 MinMaxScaler() 0 -> 0.7364063400342259
1309/3780 0.200 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5649442282290101
1310/3780 0.200 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6804635679186735
1311/3780 0.200 0.065 0.1 StandardScaler() 0 -> 0.5488526585752312
1312/3780 0.200 0.065 0.1 MinMaxScaler() 0 -> 0.6242594635646252
1313/3780 0.200 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5546856823223291
1314/3780 0.200 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5869198391515046
1315/3780 0.200 0.065 1.0 StandardScaler() 0 -> 0.5871761141480566
1316/3780 0.200 0.065 1.0 MinMaxScaler() 0 -> 0.5596185384171717
1317/3780 0.200 0.082 scale StandardScaler() 0 -> 0.5475531369508627
1318/3780 0.200 0.082 scale MinMaxScaler() 0 -> 0.5456042278855834
1319/3780 0.200 0.082 auto StandardScaler() 0 -> 0.5475531369508625
1320/3780 0.200 0.082 auto MinMaxScaler() 0 -> 0.5929776007589375
1321/3780 0.200 0.082 0.01 StandardScaler() 0 -> 0.5905421932750252
1322/3780 0.200 0.082 0.01 MinMaxScaler() 0 -> 0.7283729891139522
1323/3780 0.200 0.082 0.03162277660168379 StandardScaler() 0 -> 0.560986310863309
1324/3780 0.200 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.664219043456021
1325/3780 0.200 0.082 0.1 StandardScaler() 0 -> 0.5463406402836858
1326/3780 0.200 0.082 0.1 MinMaxScaler() 0 -> 0.6144217606487582
1327/3780 0.200 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5507334881340934
1328/3780 0.200 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5835935280225278
1329/3780 0.200 0.082 1.0 StandardScaler() 0 -> 0.5779013196826002
1330/3780 0.200 0.082 1.0 MinMaxScaler() 0 -> 0.556302578135672
1331/3780 0.200 0.104 scale StandardScaler() 0 -> 0.5453390972061837
1332/3780 0.200 0.104 scale MinMaxScaler() 0 -> 0.5433375523197139
1333/3780 0.200 0.104 auto StandardScaler() 0 -> 0.5453390972061835
1334/3780 0.200 0.104 auto MinMaxScaler() 0 -> 0.5881875870348625
1335/3780 0.200 0.104 0.01 StandardScaler() 0 -> 0.5856000120935286
1336/3780 0.200 0.104 0.01 MinMaxScaler() 0 -> 0.7185920826034061
1337/3780 0.200 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5569756213234496
1338/3780 0.200 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.651248332283955
1339/3780 0.200 0.104 0.1 StandardScaler() 0 -> 0.5441491320972127
1340/3780 0.200 0.104 0.1 MinMaxScaler() 0 -> 0.606089186776398
1341/3780 0.200 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5476456256225984
1342/3780 0.200 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.58041469002904
1343/3780 0.200 0.104 1.0 StandardScaler() 0 -> 0.569006534752568
1344/3780 0.200 0.104 1.0 MinMaxScaler() 0 -> 0.5533304199052647
1345/3780 0.200 0.132 scale StandardScaler() 0 -> 0.5435510246480645
1346/3780 0.200 0.132 scale MinMaxScaler() 0 -> 0.5416128105134582
1347/3780 0.200 0.132 auto StandardScaler() 0 -> 0.5435510246480645
1348/3780 0.200 0.132 auto MinMaxScaler() 0 -> 0.5852020992337931
1349/3780 0.200 0.132 0.01 StandardScaler() 0 -> 0.5816167652119447
1350/3780 0.200 0.132 0.01 MinMaxScaler() 0 -> 0.7068423666151554
1351/3780 0.200 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5537109653889813
1352/3780 0.200 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6412426441073295
1353/3780 0.200 0.132 0.1 StandardScaler() 0 -> 0.5427755678582603
1354/3780 0.200 0.132 0.1 MinMaxScaler() 0 -> 0.5988372301156915
1355/3780 0.200 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5443748619213347
1356/3780 0.200 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5767872700000943
1357/3780 0.200 0.132 1.0 StandardScaler() 0 -> 0.5609684699918959
1358/3780 0.200 0.132 1.0 MinMaxScaler() 0 -> 0.550421478763016
1359/3780 0.200 0.168 scale StandardScaler() 0 -> 0.5417788486243283
1360/3780 0.200 0.168 scale MinMaxScaler() 0 -> 0.5401506387217222
1361/3780 0.200 0.168 auto StandardScaler() 0 -> 0.5417788486243283
1362/3780 0.200 0.168 auto MinMaxScaler() 0 -> 0.5828236531745087
1363/3780 0.200 0.168 0.01 StandardScaler() 0 -> 0.5783404331012081
1364/3780 0.200 0.168 0.01 MinMaxScaler() 0 -> 0.6930006327247046
1365/3780 0.200 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5510873800315897
1366/3780 0.200 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6320638456235373
1367/3780 0.200 0.168 0.1 StandardScaler() 0 -> 0.5417816855853343
1368/3780 0.200 0.168 0.1 MinMaxScaler() 0 -> 0.5935012454213872
1369/3780 0.200 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5414457191398367
1370/3780 0.200 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5734908091052193
1371/3780 0.200 0.168 1.0 StandardScaler() 0 -> 0.5543368950213502
1372/3780 0.200 0.168 1.0 MinMaxScaler() 0 -> 0.5477376646166988
1373/3780 0.200 0.213 scale StandardScaler() 0 -> 0.5405305377790537
1374/3780 0.200 0.213 scale MinMaxScaler() 0 -> 0.5391223489905554
1375/3780 0.200 0.213 auto StandardScaler() 0 -> 0.5405305377790535
1376/3780 0.200 0.213 auto MinMaxScaler() 0 -> 0.5803173038372512
1377/3780 0.200 0.213 0.01 StandardScaler() 0 -> 0.5749700583623997
1378/3780 0.200 0.213 0.01 MinMaxScaler() 0 -> 0.6772558199851907
1379/3780 0.200 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5482136563353334
1380/3780 0.200 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6216828621781055
1381/3780 0.200 0.213 0.1 StandardScaler() 0 -> 0.5412162693608015
1382/3780 0.200 0.213 0.1 MinMaxScaler() 0 -> 0.5899186521891139
1383/3780 0.200 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5393488481619156
1384/3780 0.200 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.570071509904968
1385/3780 0.200 0.213 1.0 StandardScaler() 0 -> 0.5497340121458657
1386/3780 0.200 0.213 1.0 MinMaxScaler() 0 -> 0.5463415512683982
1387/3780 0.200 0.270 scale StandardScaler() 0 -> 0.5394535194062077
1388/3780 0.200 0.270 scale MinMaxScaler() 0 -> 0.5374982782234398
1389/3780 0.200 0.270 auto StandardScaler() 0 -> 0.5394535194062077
1390/3780 0.200 0.270 auto MinMaxScaler() 0 -> 0.5774738277623511
1391/3780 0.200 0.270 0.01 StandardScaler() 0 -> 0.5714722371173534
1392/3780 0.200 0.270 0.01 MinMaxScaler() 0 -> 0.6611736468009409
1393/3780 0.200 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5457050499948215
1394/3780 0.200 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6125066231806414
1395/3780 0.200 0.270 0.1 StandardScaler() 0 -> 0.5403223906614442
1396/3780 0.200 0.270 0.1 MinMaxScaler() 0 -> 0.5873937978107849
1397/3780 0.200 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5377601988557428
1398/3780 0.200 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5668741963158869
1399/3780 0.200 0.270 1.0 StandardScaler() 0 -> 0.546348652876422
1400/3780 0.200 0.270 1.0 MinMaxScaler() 0 -> 0.5439926961191933
1401/3780 0.200 0.342 scale StandardScaler() 0 -> 0.5381446465558856
1402/3780 0.200 0.342 scale MinMaxScaler() 0 -> 0.53622624134396
1403/3780 0.200 0.342 auto StandardScaler() 0 -> 0.5381446465558853
1404/3780 0.200 0.342 auto MinMaxScaler() 0 -> 0.5750341198040014
1405/3780 0.200 0.342 0.01 StandardScaler() 0 -> 0.5678446656879733
1406/3780 0.200 0.342 0.01 MinMaxScaler() 0 -> 0.649294831441745
1407/3780 0.200 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5446784511216459
1408/3780 0.200 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.6047067900211358
1409/3780 0.200 0.342 0.1 StandardScaler() 0 -> 0.5400143411029253
1410/3780 0.200 0.342 0.1 MinMaxScaler() 0 -> 0.5856366835132998
1411/3780 0.200 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5368438929246363
1412/3780 0.200 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5636175668639775
1413/3780 0.200 0.342 1.0 StandardScaler() 0 -> 0.5438041721761064
1414/3780 0.200 0.342 1.0 MinMaxScaler() 0 -> 0.5429844993331531
1415/3780 0.200 0.434 scale StandardScaler() 0 -> 0.5369186566337065
1416/3780 0.200 0.434 scale MinMaxScaler() 0 -> 0.5350443784958149
1417/3780 0.200 0.434 auto StandardScaler() 0 -> 0.5369186566337065
1418/3780 0.200 0.434 auto MinMaxScaler() 0 -> 0.5722557354743584
1419/3780 0.200 0.434 0.01 StandardScaler() 0 -> 0.564435627884874
1420/3780 0.200 0.434 0.01 MinMaxScaler() 0 -> 0.639328682611538
1421/3780 0.200 0.434 0.03162277660168379 StandardScaler() 0 -> 0.543394594344719
1422/3780 0.200 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5982325061362329
1423/3780 0.200 0.434 0.1 StandardScaler() 0 -> 0.5397031039767968
1424/3780 0.200 0.434 0.1 MinMaxScaler() 0 -> 0.5835925128744123
1425/3780 0.200 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5364720770043726
1426/3780 0.200 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5600461013094877
1427/3780 0.200 0.434 1.0 StandardScaler() 0 -> 0.5430360359465104
1428/3780 0.200 0.434 1.0 MinMaxScaler() 0 -> 0.5420091520431077
1429/3780 0.200 0.551 scale StandardScaler() 0 -> 0.536367996905677
1430/3780 0.200 0.551 scale MinMaxScaler() 0 -> 0.5350078043956604
1431/3780 0.200 0.551 auto StandardScaler() 0 -> 0.5363679969056768
1432/3780 0.200 0.551 auto MinMaxScaler() 0 -> 0.5690365048839338
1433/3780 0.200 0.551 0.01 StandardScaler() 0 -> 0.5611348328526206
1434/3780 0.200 0.551 0.01 MinMaxScaler() 0 -> 0.6300581932148538
1435/3780 0.200 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5426078759075142
1436/3780 0.200 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5935857184322911
1437/3780 0.200 0.551 0.1 StandardScaler() 0 -> 0.5389174747609883
1438/3780 0.200 0.551 0.1 MinMaxScaler() 0 -> 0.5823388779452799
1439/3780 0.200 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5365344597008611
1440/3780 0.200 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5570083999614335
1441/3780 0.200 0.551 1.0 StandardScaler() 0 -> 0.5429198454665074
1442/3780 0.200 0.551 1.0 MinMaxScaler() 0 -> 0.5413972855394444
1443/3780 0.200 0.700 scale StandardScaler() 0 -> 0.535936164418925
1444/3780 0.200 0.700 scale MinMaxScaler() 0 -> 0.5344728692149373
1445/3780 0.200 0.700 auto StandardScaler() 0 -> 0.5359361644189246
1446/3780 0.200 0.700 auto MinMaxScaler() 0 -> 0.5658150551959467
1447/3780 0.200 0.700 0.01 StandardScaler() 0 -> 0.5582934730295144
1448/3780 0.200 0.700 0.01 MinMaxScaler() 0 -> 0.6198990797351662
1449/3780 0.200 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5420481808501371
1450/3780 0.200 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5906667950226393
1451/3780 0.200 0.700 0.1 StandardScaler() 0 -> 0.5380872767734625
1452/3780 0.200 0.700 0.1 MinMaxScaler() 0 -> 0.5808791508196843
1453/3780 0.200 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5366852224450113
1454/3780 0.200 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5541596747719916
1455/3780 0.200 0.700 1.0 StandardScaler() 0 -> 0.544302463119553
1456/3780 0.200 0.700 1.0 MinMaxScaler() 0 -> 0.5413315006358052
1457/3780 0.200 0.888 scale StandardScaler() 0 -> 0.5363111086064483
1458/3780 0.200 0.888 scale MinMaxScaler() 0 -> 0.5348507088775344
1459/3780 0.200 0.888 auto StandardScaler() 0 -> 0.5363111086064484
1460/3780 0.200 0.888 auto MinMaxScaler() 0 -> 0.5624117733791295
1461/3780 0.200 0.888 0.01 StandardScaler() 0 -> 0.5556111313736009
1462/3780 0.200 0.888 0.01 MinMaxScaler() 0 -> 0.6112233881530905
1463/3780 0.200 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5422125065193796
1464/3780 0.200 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5888740438630251
1465/3780 0.200 0.888 0.1 StandardScaler() 0 -> 0.5378964545363285
1466/3780 0.200 0.888 0.1 MinMaxScaler() 0 -> 0.5788401613904166
1467/3780 0.200 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5386161153017
1468/3780 0.200 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5524086723746694
1469/3780 0.200 0.888 1.0 StandardScaler() 0 -> 0.5480027652787846
1470/3780 0.200 0.888 1.0 MinMaxScaler() 0 -> 0.5409045193479766
1471/3780 0.200 1.126 scale StandardScaler() 0 -> 0.5372746719318428
1472/3780 0.200 1.126 scale MinMaxScaler() 0 -> 0.5353193928662812
1473/3780 0.200 1.126 auto StandardScaler() 0 -> 0.5372746719318425
1474/3780 0.200 1.126 auto MinMaxScaler() 0 -> 0.5590556673943611
1475/3780 0.200 1.126 0.01 StandardScaler() 0 -> 0.5532809624441258
1476/3780 0.200 1.126 0.01 MinMaxScaler() 0 -> 0.6034319104827373
1477/3780 0.200 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5418805097462908
1478/3780 0.200 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5875940600825502
1479/3780 0.200 1.126 0.1 StandardScaler() 0 -> 0.5375453881596867
1480/3780 0.200 1.126 0.1 MinMaxScaler() 0 -> 0.5765641085196443
1481/3780 0.200 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5408923783445193
1482/3780 0.200 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5501861066283694
1483/3780 0.200 1.126 1.0 StandardScaler() 0 -> 0.5527368961221036
1484/3780 0.200 1.126 1.0 MinMaxScaler() 0 -> 0.5410104211519797
1485/3780 0.200 1.429 scale StandardScaler() 0 -> 0.5383768951240945
1486/3780 0.200 1.429 scale MinMaxScaler() 0 -> 0.5365943287770134
1487/3780 0.200 1.429 auto StandardScaler() 0 -> 0.5383768951240943
1488/3780 0.200 1.429 auto MinMaxScaler() 0 -> 0.556057410632713
1489/3780 0.200 1.429 0.01 StandardScaler() 0 -> 0.5502649579696587
1490/3780 0.200 1.429 0.01 MinMaxScaler() 0 -> 0.5972291574558528
1491/3780 0.200 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5415163975716245
1492/3780 0.200 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5866224955575373
1493/3780 0.200 1.429 0.1 StandardScaler() 0 -> 0.5376504571330994
1494/3780 0.200 1.429 0.1 MinMaxScaler() 0 -> 0.5741870359588382
1495/3780 0.200 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5427616674707546
1496/3780 0.200 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5482256985952841
1497/3780 0.200 1.429 1.0 StandardScaler() 0 -> 0.5599078100088337
1498/3780 0.200 1.429 1.0 MinMaxScaler() 0 -> 0.5407158768725554
1499/3780 0.200 1.814 scale StandardScaler() 0 -> 0.5401089981115237
1500/3780 0.200 1.814 scale MinMaxScaler() 0 -> 0.5381033469130588
1501/3780 0.200 1.814 auto StandardScaler() 0 -> 0.5401089981115241
1502/3780 0.200 1.814 auto MinMaxScaler() 0 -> 0.5534553527751194
1503/3780 0.200 1.814 0.01 StandardScaler() 0 -> 0.5479312436819023
1504/3780 0.200 1.814 0.01 MinMaxScaler() 0 -> 0.5934077309862283
1505/3780 0.200 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5414293240301643
1506/3780 0.200 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5862856239589772
1507/3780 0.200 1.814 0.1 StandardScaler() 0 -> 0.5377182793169138
1508/3780 0.200 1.814 0.1 MinMaxScaler() 0 -> 0.5716565887047619
1509/3780 0.200 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5449955741832148
1510/3780 0.200 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5459211363002595
1511/3780 0.200 1.814 1.0 StandardScaler() 0 -> 0.5681583602713303
1512/3780 0.200 1.814 1.0 MinMaxScaler() 0 -> 0.5405703100054553
1513/3780 0.200 2.302 scale StandardScaler() 0 -> 0.5421091336483993
1514/3780 0.200 2.302 scale MinMaxScaler() 0 -> 0.5395643661697217
1515/3780 0.200 2.302 auto StandardScaler() 0 -> 0.5421091336483997
1516/3780 0.200 2.302 auto MinMaxScaler() 0 -> 0.5520355879393469
1517/3780 0.200 2.302 0.01 StandardScaler() 0 -> 0.5461165128201307
1518/3780 0.200 2.302 0.01 MinMaxScaler() 0 -> 0.5909043627703778
1519/3780 0.200 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5415801555659852
1520/3780 0.200 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5854240258824426
1521/3780 0.200 2.302 0.1 StandardScaler() 0 -> 0.5382216562139768
1522/3780 0.200 2.302 0.1 MinMaxScaler() 0 -> 0.5687251033636863
1523/3780 0.200 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5486176480652619
1524/3780 0.200 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.544316692999263
1525/3780 0.200 2.302 1.0 StandardScaler() 0 -> 0.5759239949450538
1526/3780 0.200 2.302 1.0 MinMaxScaler() 0 -> 0.5407694980156865
1527/3780 0.200 2.921 scale StandardScaler() 0 -> 0.5448973538850961
1528/3780 0.200 2.921 scale MinMaxScaler() 0 -> 0.5413642546200124
1529/3780 0.200 2.921 auto StandardScaler() 0 -> 0.5448973538850952
1530/3780 0.200 2.921 auto MinMaxScaler() 0 -> 0.5499653275995167
1531/3780 0.200 2.921 0.01 StandardScaler() 0 -> 0.5449864857386899
1532/3780 0.200 2.921 0.01 MinMaxScaler() 0 -> 0.5893455764953097
1533/3780 0.200 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5414650278704162
1534/3780 0.200 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5844492919531382
1535/3780 0.200 2.921 0.1 StandardScaler() 0 -> 0.5381160630927839
1536/3780 0.200 2.921 0.1 MinMaxScaler() 0 -> 0.5650797422289069
1537/3780 0.200 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5534423689834383
1538/3780 0.200 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5437255112270822
1539/3780 0.200 2.921 1.0 StandardScaler() 0 -> 0.5860033536220667
1540/3780 0.200 2.921 1.0 MinMaxScaler() 0 -> 0.5407768362288313
1541/3780 0.200 3.707 scale StandardScaler() 0 -> 0.5471276215369115
1542/3780 0.200 3.707 scale MinMaxScaler() 0 -> 0.5434405047884683
1543/3780 0.200 3.707 auto StandardScaler() 0 -> 0.5471276215369105
1544/3780 0.200 3.707 auto MinMaxScaler() 0 -> 0.5480609117253875
1545/3780 0.200 3.707 0.01 StandardScaler() 0 -> 0.5450334125936281
1546/3780 0.200 3.707 0.01 MinMaxScaler() 0 -> 0.5881806935128239
1547/3780 0.200 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5413785478106267
1548/3780 0.200 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5836196869936807
1549/3780 0.200 3.707 0.1 StandardScaler() 0 -> 0.5388893438885743
1550/3780 0.200 3.707 0.1 MinMaxScaler() 0 -> 0.5614872233763709
1551/3780 0.200 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5582344905517375
1552/3780 0.200 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5435466679192685
1553/3780 0.200 3.707 1.0 StandardScaler() 0 -> 0.5953165038783482
1554/3780 0.200 3.707 1.0 MinMaxScaler() 0 -> 0.5406391105752218
1555/3780 0.200 4.703 scale StandardScaler() 0 -> 0.5496253149422529
1556/3780 0.200 4.703 scale MinMaxScaler() 0 -> 0.5472485411913853
1557/3780 0.200 4.703 auto StandardScaler() 0 -> 0.5496253149422513
1558/3780 0.200 4.703 auto MinMaxScaler() 0 -> 0.5460978479862281
1559/3780 0.200 4.703 0.01 StandardScaler() 0 -> 0.5448834565844739
1560/3780 0.200 4.703 0.01 MinMaxScaler() 0 -> 0.5876751700624278
1561/3780 0.200 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5410823653509366
1562/3780 0.200 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5826438447472639
1563/3780 0.200 4.703 0.1 StandardScaler() 0 -> 0.5402096637402404
1564/3780 0.200 4.703 0.1 MinMaxScaler() 0 -> 0.558236838312606
1565/3780 0.200 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5627302494203507
1566/3780 0.200 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5433470517744988
1567/3780 0.200 4.703 1.0 StandardScaler() 0 -> 0.6065607438267152
1568/3780 0.200 4.703 1.0 MinMaxScaler() 0 -> 0.5403742487587017
1569/3780 0.200 5.968 scale StandardScaler() 0 -> 0.5526743548564895
1570/3780 0.200 5.968 scale MinMaxScaler() 0 -> 0.550282183464672
1571/3780 0.200 5.968 auto StandardScaler() 0 -> 0.5526743548564917
1572/3780 0.200 5.968 auto MinMaxScaler() 0 -> 0.5448549288759926
1573/3780 0.200 5.968 0.01 StandardScaler() 0 -> 0.5445765503429998
1574/3780 0.200 5.968 0.01 MinMaxScaler() 0 -> 0.5875676990407972
1575/3780 0.200 5.968 0.03162277660168379 StandardScaler() 0 -> 0.540606608716476
1576/3780 0.200 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5814386534750943
1577/3780 0.200 5.968 0.1 StandardScaler() 0 -> 0.5411770840484271
1578/3780 0.200 5.968 0.1 MinMaxScaler() 0 -> 0.5555487612135611
1579/3780 0.200 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5687048481504176
1580/3780 0.200 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.543415253643586
1581/3780 0.200 5.968 1.0 StandardScaler() 0 -> 0.6199592277714714
1582/3780 0.200 5.968 1.0 MinMaxScaler() 0 -> 0.5402325914008701
1583/3780 0.200 7.574 scale StandardScaler() 0 -> 0.5566998266729279
1584/3780 0.200 7.574 scale MinMaxScaler() 0 -> 0.5532377256686937
1585/3780 0.200 7.574 auto StandardScaler() 0 -> 0.5566998266729297
1586/3780 0.200 7.574 auto MinMaxScaler() 0 -> 0.5444234521099433
1587/3780 0.200 7.574 0.01 StandardScaler() 0 -> 0.5444959343408423
1588/3780 0.200 7.574 0.01 MinMaxScaler() 0 -> 0.5870790861012443
1589/3780 0.200 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5398093356728083
1590/3780 0.200 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.579970149120692
1591/3780 0.200 7.574 0.1 StandardScaler() 0 -> 0.5432861122654397
1592/3780 0.200 7.574 0.1 MinMaxScaler() 0 -> 0.5532666888277004
1593/3780 0.200 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5765160596034099
1594/3780 0.200 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5434802849036877
1595/3780 0.200 7.574 1.0 StandardScaler() 0 -> 0.6356040155967713
1596/3780 0.200 7.574 1.0 MinMaxScaler() 0 -> 0.54024100250229
1597/3780 0.200 9.611 scale StandardScaler() 0 -> 0.561482468986499
1598/3780 0.200 9.611 scale MinMaxScaler() 0 -> 0.5571520866383007
1599/3780 0.200 9.611 auto StandardScaler() 0 -> 0.5614824689864921
1600/3780 0.200 9.611 auto MinMaxScaler() 0 -> 0.5443537178631385
1601/3780 0.200 9.611 0.01 StandardScaler() 0 -> 0.5443940961218234
1602/3780 0.200 9.611 0.01 MinMaxScaler() 0 -> 0.5868637236068621
1603/3780 0.200 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5398267012885632
1604/3780 0.200 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5781565488357789
1605/3780 0.200 9.611 0.1 StandardScaler() 0 -> 0.5446050881142516
1606/3780 0.200 9.611 0.1 MinMaxScaler() 0 -> 0.5518096573880605
1607/3780 0.200 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5834562029021234
1608/3780 0.200 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5434472826585979
1609/3780 0.200 9.611 1.0 StandardScaler() 0 -> 0.6525103158274604
1610/3780 0.200 9.611 1.0 MinMaxScaler() 0 -> 0.5399999554047792
1611/3780 0.200 12.196 scale StandardScaler() 0 -> 0.5670412331373048
1612/3780 0.200 12.196 scale MinMaxScaler() 0 -> 0.5611860841004997
1613/3780 0.200 12.196 auto StandardScaler() 0 -> 0.5670412331373047
1614/3780 0.200 12.196 auto MinMaxScaler() 0 -> 0.5441762766074435
1615/3780 0.200 12.196 0.01 StandardScaler() 0 -> 0.5443358600215563
1616/3780 0.200 12.196 0.01 MinMaxScaler() 0 -> 0.5865235832468386
1617/3780 0.200 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5397092528110692
1618/3780 0.200 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5761186162178272
1619/3780 0.200 12.196 0.1 StandardScaler() 0 -> 0.5462003343973568
1620/3780 0.200 12.196 0.1 MinMaxScaler() 0 -> 0.5498674980760621
1621/3780 0.200 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5906626164365546
1622/3780 0.200 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5433119703877044
1623/3780 0.200 12.196 1.0 StandardScaler() 0 -> 0.6713242932384359
1624/3780 0.200 12.196 1.0 MinMaxScaler() 0 -> 0.5397183913327064
1625/3780 0.200 15.476 scale StandardScaler() 0 -> 0.5730206976304498
1626/3780 0.200 15.476 scale MinMaxScaler() 0 -> 0.565037114008912
1627/3780 0.200 15.476 auto StandardScaler() 0 -> 0.5730206976304534
1628/3780 0.200 15.476 auto MinMaxScaler() 0 -> 0.5443102967612344
1629/3780 0.200 15.476 0.01 StandardScaler() 0 -> 0.5446701408800761
1630/3780 0.200 15.476 0.01 MinMaxScaler() 0 -> 0.5862419097890729
1631/3780 0.200 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5394751365906457
1632/3780 0.200 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5733994419002474
1633/3780 0.200 15.476 0.1 StandardScaler() 0 -> 0.5468001709913344
1634/3780 0.200 15.476 0.1 MinMaxScaler() 0 -> 0.5481017931201427
1635/3780 0.200 15.476 0.31622776601683794 StandardScaler() 0 -> 0.599176136355052
1636/3780 0.200 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5432052656738001
1637/3780 0.200 15.476 1.0 StandardScaler() 0 -> 0.6931946650206419
1638/3780 0.200 15.476 1.0 MinMaxScaler() 0 -> 0.5397775469758442
1639/3780 0.200 19.638 scale StandardScaler() 0 -> 0.5806778382712822
1640/3780 0.200 19.638 scale MinMaxScaler() 0 -> 0.568444048334317
1641/3780 0.200 19.638 auto StandardScaler() 0 -> 0.5806778382712813
1642/3780 0.200 19.638 auto MinMaxScaler() 0 -> 0.5443916340179186
1643/3780 0.200 19.638 0.01 StandardScaler() 0 -> 0.5445547805661692
1644/3780 0.200 19.638 0.01 MinMaxScaler() 0 -> 0.5859027663662455
1645/3780 0.200 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5399371335975555
1646/3780 0.200 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5708790738991212
1647/3780 0.200 19.638 0.1 StandardScaler() 0 -> 0.5486240103602955
1648/3780 0.200 19.638 0.1 MinMaxScaler() 0 -> 0.546303954167929
1649/3780 0.200 19.638 0.31622776601683794 StandardScaler() 0 -> 0.6100553671104477
1650/3780 0.200 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5431329661090661
1651/3780 0.200 19.638 1.0 StandardScaler() 0 -> 0.7175252352166593
1652/3780 0.200 19.638 1.0 MinMaxScaler() 0 -> 0.5397155000445345
1653/3780 0.200 24.920 scale StandardScaler() 0 -> 0.5886529856902555
1654/3780 0.200 24.920 scale MinMaxScaler() 0 -> 0.572918027852096
1655/3780 0.200 24.920 auto StandardScaler() 0 -> 0.5886529856902488
1656/3780 0.200 24.920 auto MinMaxScaler() 0 -> 0.5443078192908449
1657/3780 0.200 24.920 0.01 StandardScaler() 0 -> 0.5447623701779672
1658/3780 0.200 24.920 0.01 MinMaxScaler() 0 -> 0.585219009393061
1659/3780 0.200 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5402619940997816
1660/3780 0.200 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5674372316021405
1661/3780 0.200 24.920 0.1 StandardScaler() 0 -> 0.551990243369201
1662/3780 0.200 24.920 0.1 MinMaxScaler() 0 -> 0.5456974000192568
1663/3780 0.200 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6232589452619252
1664/3780 0.200 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.543156755696747
1665/3780 0.200 24.920 1.0 StandardScaler() 0 -> 0.7453315743287258
1666/3780 0.200 24.920 1.0 MinMaxScaler() 0 -> 0.5398326078791408
1667/3780 0.200 31.623 scale StandardScaler() 0 -> 0.5970282070780498
1668/3780 0.200 31.623 scale MinMaxScaler() 0 -> 0.5778350962172735
1669/3780 0.200 31.623 auto StandardScaler() 0 -> 0.5970282070780683
1670/3780 0.200 31.623 auto MinMaxScaler() 0 -> 0.5440918290453978
1671/3780 0.200 31.623 0.01 StandardScaler() 0 -> 0.5445626558874181
1672/3780 0.200 31.623 0.01 MinMaxScaler() 0 -> 0.5846219425622063
1673/3780 0.200 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5407005569319915
1674/3780 0.200 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5636542615086481
1675/3780 0.200 31.623 0.1 StandardScaler() 0 -> 0.5555782174054918
1676/3780 0.200 31.623 0.1 MinMaxScaler() 0 -> 0.5451229774360122
1677/3780 0.200 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6388532203077223
1678/3780 0.200 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5431298463896302
1679/3780 0.200 31.623 1.0 StandardScaler() 0 -> 0.7745271376339066
1680/3780 0.200 31.623 1.0 MinMaxScaler() 0 -> 0.5401577534190921
1681/3780 0.250 0.032 scale StandardScaler() 0 -> 0.5602781187578453
1682/3780 0.250 0.032 scale MinMaxScaler() 0 -> 0.556742682121054
1683/3780 0.250 0.032 auto StandardScaler() 0 -> 0.5602781187578453
1684/3780 0.250 0.032 auto MinMaxScaler() 0 -> 0.6173120184238532
1685/3780 0.250 0.032 0.01 StandardScaler() 0 -> 0.6136953086375486
1686/3780 0.250 0.032 0.01 MinMaxScaler() 0 -> 0.7648763163408893
1687/3780 0.250 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5794322947650318
1688/3780 0.250 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7302558598123974
1689/3780 0.250 0.032 0.1 StandardScaler() 0 -> 0.5590494886851292
1690/3780 0.250 0.032 0.1 MinMaxScaler() 0 -> 0.6517080203322411
1691/3780 0.250 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5671004972888958
1692/3780 0.250 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6004283283500623
1693/3780 0.250 0.032 1.0 StandardScaler() 0 -> 0.6227788122282772
1694/3780 0.250 0.032 1.0 MinMaxScaler() 0 -> 0.5725706197787609
1695/3780 0.250 0.040 scale StandardScaler() 0 -> 0.5560884327623017
1696/3780 0.250 0.040 scale MinMaxScaler() 0 -> 0.5529798120834213
1697/3780 0.250 0.040 auto StandardScaler() 0 -> 0.5560884327623016
1698/3780 0.250 0.040 auto MinMaxScaler() 0 -> 0.6077908704170493
1699/3780 0.250 0.040 0.01 StandardScaler() 0 -> 0.6048466881482796
1700/3780 0.250 0.040 0.01 MinMaxScaler() 0 -> 0.7602776135791901
1701/3780 0.250 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5740776198198253
1702/3780 0.250 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7177301152267838
1703/3780 0.250 0.040 0.1 StandardScaler() 0 -> 0.5553530029864264
1704/3780 0.250 0.040 0.1 MinMaxScaler() 0 -> 0.6353008803308554
1705/3780 0.250 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5618224145008228
1706/3780 0.250 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5940346699387054
1707/3780 0.250 0.040 1.0 StandardScaler() 0 -> 0.6084277305429059
1708/3780 0.250 0.040 1.0 MinMaxScaler() 0 -> 0.5676128581282315
1709/3780 0.250 0.051 scale StandardScaler() 0 -> 0.5522352601661321
1710/3780 0.250 0.051 scale MinMaxScaler() 0 -> 0.5500042512188208
1711/3780 0.250 0.051 auto StandardScaler() 0 -> 0.5522352601661321
1712/3780 0.250 0.051 auto MinMaxScaler() 0 -> 0.5999271416987685
1713/3780 0.250 0.051 0.01 StandardScaler() 0 -> 0.597167016688885
1714/3780 0.250 0.051 0.01 MinMaxScaler() 0 -> 0.7545407575034981
1715/3780 0.250 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5695631432130338
1716/3780 0.250 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.702850289916825
1717/3780 0.250 0.051 0.1 StandardScaler() 0 -> 0.551333985168342
1718/3780 0.250 0.051 0.1 MinMaxScaler() 0 -> 0.6244700031612168
1719/3780 0.250 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5570449563188419
1720/3780 0.250 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5887841022067657
1721/3780 0.250 0.051 1.0 StandardScaler() 0 -> 0.5959414889113483
1722/3780 0.250 0.051 1.0 MinMaxScaler() 0 -> 0.5637203402282139
1723/3780 0.250 0.065 scale StandardScaler() 0 -> 0.5492433383924139
1724/3780 0.250 0.065 scale MinMaxScaler() 0 -> 0.5473487503256512
1725/3780 0.250 0.065 auto StandardScaler() 0 -> 0.5492433383924139
1726/3780 0.250 0.065 auto MinMaxScaler() 0 -> 0.5940410325424259
1727/3780 0.250 0.065 0.01 StandardScaler() 0 -> 0.5914543506506743
1728/3780 0.250 0.065 0.01 MinMaxScaler() 0 -> 0.7474198733440461
1729/3780 0.250 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5649656553072099
1730/3780 0.250 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6855313328282455
1731/3780 0.250 0.065 0.1 StandardScaler() 0 -> 0.5486471913528053
1732/3780 0.250 0.065 0.1 MinMaxScaler() 0 -> 0.6155512840872377
1733/3780 0.250 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5525965216623487
1734/3780 0.250 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5850478387361081
1735/3780 0.250 0.065 1.0 StandardScaler() 0 -> 0.584889541662056
1736/3780 0.250 0.065 1.0 MinMaxScaler() 0 -> 0.560729360982414
1737/3780 0.250 0.082 scale StandardScaler() 0 -> 0.5467886476009648
1738/3780 0.250 0.082 scale MinMaxScaler() 0 -> 0.5453431220845443
1739/3780 0.250 0.082 auto StandardScaler() 0 -> 0.5467886476009649
1740/3780 0.250 0.082 auto MinMaxScaler() 0 -> 0.5893025177291599
1741/3780 0.250 0.082 0.01 StandardScaler() 0 -> 0.5871431803532291
1742/3780 0.250 0.082 0.01 MinMaxScaler() 0 -> 0.7386427610136419
1743/3780 0.250 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5616472642235065
1744/3780 0.250 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6660786179208156
1745/3780 0.250 0.082 0.1 StandardScaler() 0 -> 0.5454277493763446
1746/3780 0.250 0.082 0.1 MinMaxScaler() 0 -> 0.60620304698115
1747/3780 0.250 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5496021537914447
1748/3780 0.250 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5813055076302395
1749/3780 0.250 0.082 1.0 StandardScaler() 0 -> 0.574693793060649
1750/3780 0.250 0.082 1.0 MinMaxScaler() 0 -> 0.5572780758787282
1751/3780 0.250 0.104 scale StandardScaler() 0 -> 0.5446035885664543
1752/3780 0.250 0.104 scale MinMaxScaler() 0 -> 0.5430261647308553
1753/3780 0.250 0.104 auto StandardScaler() 0 -> 0.5446035885664542
1754/3780 0.250 0.104 auto MinMaxScaler() 0 -> 0.5865419426132795
1755/3780 0.250 0.104 0.01 StandardScaler() 0 -> 0.5833347306191198
1756/3780 0.250 0.104 0.01 MinMaxScaler() 0 -> 0.7279102292318451
1757/3780 0.250 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5580928971157958
1758/3780 0.250 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6464348923848141
1759/3780 0.250 0.104 0.1 StandardScaler() 0 -> 0.5434900649890785
1760/3780 0.250 0.104 0.1 MinMaxScaler() 0 -> 0.5991844339471594
1761/3780 0.250 0.104 0.31622776601683794 StandardScaler() 0 -> 0.546449789375158
1762/3780 0.250 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5789795604252311
1763/3780 0.250 0.104 1.0 StandardScaler() 0 -> 0.5666854736746375
1764/3780 0.250 0.104 1.0 MinMaxScaler() 0 -> 0.553882609717188
1765/3780 0.250 0.132 scale StandardScaler() 0 -> 0.542584715806374
1766/3780 0.250 0.132 scale MinMaxScaler() 0 -> 0.5410870524921617
1767/3780 0.250 0.132 auto StandardScaler() 0 -> 0.5425847158063742
1768/3780 0.250 0.132 auto MinMaxScaler() 0 -> 0.583379116529224
1769/3780 0.250 0.132 0.01 StandardScaler() 0 -> 0.5804040315422703
1770/3780 0.250 0.132 0.01 MinMaxScaler() 0 -> 0.7149618861354295
1771/3780 0.250 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5551182244085108
1772/3780 0.250 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6323749970501145
1773/3780 0.250 0.132 0.1 StandardScaler() 0 -> 0.5425339565195525
1774/3780 0.250 0.132 0.1 MinMaxScaler() 0 -> 0.5940510890471737
1775/3780 0.250 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5437062346112337
1776/3780 0.250 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5759786399708303
1777/3780 0.250 0.132 1.0 StandardScaler() 0 -> 0.5595620942874623
1778/3780 0.250 0.132 1.0 MinMaxScaler() 0 -> 0.5510714482683857
1779/3780 0.250 0.168 scale StandardScaler() 0 -> 0.5410745294761907
1780/3780 0.250 0.168 scale MinMaxScaler() 0 -> 0.5396590598484196
1781/3780 0.250 0.168 auto StandardScaler() 0 -> 0.5410745294761906
1782/3780 0.250 0.168 auto MinMaxScaler() 0 -> 0.5813531338149756
1783/3780 0.250 0.168 0.01 StandardScaler() 0 -> 0.5773125619845206
1784/3780 0.250 0.168 0.01 MinMaxScaler() 0 -> 0.6995949732544015
1785/3780 0.250 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5514451733516973
1786/3780 0.250 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6219637680908302
1787/3780 0.250 0.168 0.1 StandardScaler() 0 -> 0.5408493104187437
1788/3780 0.250 0.168 0.1 MinMaxScaler() 0 -> 0.5902857710078426
1789/3780 0.250 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5409759203976234
1790/3780 0.250 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5730694399683162
1791/3780 0.250 0.168 1.0 StandardScaler() 0 -> 0.5532171148834064
1792/3780 0.250 0.168 1.0 MinMaxScaler() 0 -> 0.548807143524824
1793/3780 0.250 0.213 scale StandardScaler() 0 -> 0.5400017407542443
1794/3780 0.250 0.213 scale MinMaxScaler() 0 -> 0.5384023413674829
1795/3780 0.250 0.213 auto StandardScaler() 0 -> 0.5400017407542442
1796/3780 0.250 0.213 auto MinMaxScaler() 0 -> 0.5791547819727166
1797/3780 0.250 0.213 0.01 StandardScaler() 0 -> 0.5746643520001529
1798/3780 0.250 0.213 0.01 MinMaxScaler() 0 -> 0.6817715120358039
1799/3780 0.250 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5489134950712763
1800/3780 0.250 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6131678928446441
1801/3780 0.250 0.213 0.1 StandardScaler() 0 -> 0.5403914092498081
1802/3780 0.250 0.213 0.1 MinMaxScaler() 0 -> 0.5881590440248515
1803/3780 0.250 0.213 0.31622776601683794 StandardScaler() 0 -> 0.539178316691558
1804/3780 0.250 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5701063847683393
1805/3780 0.250 0.213 1.0 StandardScaler() 0 -> 0.5490515325124878
1806/3780 0.250 0.213 1.0 MinMaxScaler() 0 -> 0.5468390645045474
1807/3780 0.250 0.270 scale StandardScaler() 0 -> 0.53873699819247
1808/3780 0.250 0.270 scale MinMaxScaler() 0 -> 0.5369857448236316
1809/3780 0.250 0.270 auto StandardScaler() 0 -> 0.5387369981924698
1810/3780 0.250 0.270 auto MinMaxScaler() 0 -> 0.5769451753831668
1811/3780 0.250 0.270 0.01 StandardScaler() 0 -> 0.5716779202780168
1812/3780 0.250 0.270 0.01 MinMaxScaler() 0 -> 0.6622352252746646
1813/3780 0.250 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5471307747536063
1814/3780 0.250 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6045728472999253
1815/3780 0.250 0.270 0.1 StandardScaler() 0 -> 0.5396564337944102
1816/3780 0.250 0.270 0.1 MinMaxScaler() 0 -> 0.5856663064323541
1817/3780 0.250 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5374037837240309
1818/3780 0.250 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5669018548573393
1819/3780 0.250 0.270 1.0 StandardScaler() 0 -> 0.5452421652606139
1820/3780 0.250 0.270 1.0 MinMaxScaler() 0 -> 0.5447924682257962
1821/3780 0.250 0.342 scale StandardScaler() 0 -> 0.5372729728743665
1822/3780 0.250 0.342 scale MinMaxScaler() 0 -> 0.5357000694114421
1823/3780 0.250 0.342 auto StandardScaler() 0 -> 0.5372729728743663
1824/3780 0.250 0.342 auto MinMaxScaler() 0 -> 0.5745126216643562
1825/3780 0.250 0.342 0.01 StandardScaler() 0 -> 0.5685730130863619
1826/3780 0.250 0.342 0.01 MinMaxScaler() 0 -> 0.6430928958774774
1827/3780 0.250 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5450156148989503
1828/3780 0.250 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5983565112985683
1829/3780 0.250 0.342 0.1 StandardScaler() 0 -> 0.5388020820534041
1830/3780 0.250 0.342 0.1 MinMaxScaler() 0 -> 0.5840120914195382
1831/3780 0.250 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5358361759105174
1832/3780 0.250 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5641835216421419
1833/3780 0.250 0.342 1.0 StandardScaler() 0 -> 0.5430101692512125
1834/3780 0.250 0.342 1.0 MinMaxScaler() 0 -> 0.5428538608162009
1835/3780 0.250 0.434 scale StandardScaler() 0 -> 0.5359983162923769
1836/3780 0.250 0.434 scale MinMaxScaler() 0 -> 0.535351189436967
1837/3780 0.250 0.434 auto StandardScaler() 0 -> 0.5359983162923769
1838/3780 0.250 0.434 auto MinMaxScaler() 0 -> 0.571774815023533
1839/3780 0.250 0.434 0.01 StandardScaler() 0 -> 0.565169047495175
1840/3780 0.250 0.434 0.01 MinMaxScaler() 0 -> 0.6302067093100964
1841/3780 0.250 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5433462812425754
1842/3780 0.250 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5937115137224444
1843/3780 0.250 0.434 0.1 StandardScaler() 0 -> 0.5377147173092423
1844/3780 0.250 0.434 0.1 MinMaxScaler() 0 -> 0.582651552955988
1845/3780 0.250 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5354716356159693
1846/3780 0.250 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5613504473172715
1847/3780 0.250 0.434 1.0 StandardScaler() 0 -> 0.5420679858475719
1848/3780 0.250 0.434 1.0 MinMaxScaler() 0 -> 0.5411848539930096
1849/3780 0.250 0.551 scale StandardScaler() 0 -> 0.5359041013430196
1850/3780 0.250 0.551 scale MinMaxScaler() 0 -> 0.5344061853263309
1851/3780 0.250 0.551 auto StandardScaler() 0 -> 0.5359041013430196
1852/3780 0.250 0.551 auto MinMaxScaler() 0 -> 0.5690368658433754
1853/3780 0.250 0.551 0.01 StandardScaler() 0 -> 0.5622466902023618
1854/3780 0.250 0.551 0.01 MinMaxScaler() 0 -> 0.6203359259469122
1855/3780 0.250 0.551 0.03162277660168379 StandardScaler() 0 -> 0.541633479036522
1856/3780 0.250 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.590890798678668
1857/3780 0.250 0.551 0.1 StandardScaler() 0 -> 0.5365453108267859
1858/3780 0.250 0.551 0.1 MinMaxScaler() 0 -> 0.5812197633204188
1859/3780 0.250 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5351986026951207
1860/3780 0.250 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.558528452598129
1861/3780 0.250 0.551 1.0 StandardScaler() 0 -> 0.5412838279091824
1862/3780 0.250 0.551 1.0 MinMaxScaler() 0 -> 0.5404970093034266
1863/3780 0.250 0.700 scale StandardScaler() 0 -> 0.5362551321605716
1864/3780 0.250 0.700 scale MinMaxScaler() 0 -> 0.5337356119838635
1865/3780 0.250 0.700 auto StandardScaler() 0 -> 0.5362551321605712
1866/3780 0.250 0.700 auto MinMaxScaler() 0 -> 0.5661282939127622
1867/3780 0.250 0.700 0.01 StandardScaler() 0 -> 0.558943393676052
1868/3780 0.250 0.700 0.01 MinMaxScaler() 0 -> 0.6116048944134079
1869/3780 0.250 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5409056673977719
1870/3780 0.250 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5889663295594353
1871/3780 0.250 0.700 0.1 StandardScaler() 0 -> 0.5362531379652367
1872/3780 0.250 0.700 0.1 MinMaxScaler() 0 -> 0.5797626737185296
1873/3780 0.250 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5348185529366699
1874/3780 0.250 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5560562594847418
1875/3780 0.250 0.700 1.0 StandardScaler() 0 -> 0.5422709291469673
1876/3780 0.250 0.700 1.0 MinMaxScaler() 0 -> 0.539715980369089
1877/3780 0.250 0.888 scale StandardScaler() 0 -> 0.5363414971453196
1878/3780 0.250 0.888 scale MinMaxScaler() 0 -> 0.5340557172181744
1879/3780 0.250 0.888 auto StandardScaler() 0 -> 0.5363414971453196
1880/3780 0.250 0.888 auto MinMaxScaler() 0 -> 0.5635061569106616
1881/3780 0.250 0.888 0.01 StandardScaler() 0 -> 0.556941124984049
1882/3780 0.250 0.888 0.01 MinMaxScaler() 0 -> 0.6034797611439702
1883/3780 0.250 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5404240570698904
1884/3780 0.250 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5876627142174325
1885/3780 0.250 0.888 0.1 StandardScaler() 0 -> 0.536475406039404
1886/3780 0.250 0.888 0.1 MinMaxScaler() 0 -> 0.5780276728815282
1887/3780 0.250 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5368983706904417
1888/3780 0.250 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5538144476573148
1889/3780 0.250 0.888 1.0 StandardScaler() 0 -> 0.545201774187333
1890/3780 0.250 0.888 1.0 MinMaxScaler() 0 -> 0.5393038547887472
1891/3780 0.250 1.126 scale StandardScaler() 0 -> 0.5371071845126548
1892/3780 0.250 1.126 scale MinMaxScaler() 0 -> 0.5347277107930766
1893/3780 0.250 1.126 auto StandardScaler() 0 -> 0.5371071845126545
1894/3780 0.250 1.126 auto MinMaxScaler() 0 -> 0.560563931673205
1895/3780 0.250 1.126 0.01 StandardScaler() 0 -> 0.5538463532440477
1896/3780 0.250 1.126 0.01 MinMaxScaler() 0 -> 0.5976844426424712
1897/3780 0.250 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5402098462512436
1898/3780 0.250 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5865042999073299
1899/3780 0.250 1.126 0.1 StandardScaler() 0 -> 0.5369845533665938
1900/3780 0.250 1.126 0.1 MinMaxScaler() 0 -> 0.5761138252782102
1901/3780 0.250 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5392999382505924
1902/3780 0.250 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5511527053680546
1903/3780 0.250 1.126 1.0 StandardScaler() 0 -> 0.5502704164164826
1904/3780 0.250 1.126 1.0 MinMaxScaler() 0 -> 0.5390490328914512
1905/3780 0.250 1.429 scale StandardScaler() 0 -> 0.5378580857154139
1906/3780 0.250 1.429 scale MinMaxScaler() 0 -> 0.5358407272062143
1907/3780 0.250 1.429 auto StandardScaler() 0 -> 0.5378580857154135
1908/3780 0.250 1.429 auto MinMaxScaler() 0 -> 0.5574498987448574
1909/3780 0.250 1.429 0.01 StandardScaler() 0 -> 0.5511945661625154
1910/3780 0.250 1.429 0.01 MinMaxScaler() 0 -> 0.5934007779371353
1911/3780 0.250 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5401816722234134
1912/3780 0.250 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5855342937716328
1913/3780 0.250 1.429 0.1 StandardScaler() 0 -> 0.5369540476714696
1914/3780 0.250 1.429 0.1 MinMaxScaler() 0 -> 0.5738230245260297
1915/3780 0.250 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5411927449552337
1916/3780 0.250 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.548962087084255
1917/3780 0.250 1.429 1.0 StandardScaler() 0 -> 0.5565741302415833
1918/3780 0.250 1.429 1.0 MinMaxScaler() 0 -> 0.5390130715676072
1919/3780 0.250 1.814 scale StandardScaler() 0 -> 0.5390361364389089
1920/3780 0.250 1.814 scale MinMaxScaler() 0 -> 0.5366389177836167
1921/3780 0.250 1.814 auto StandardScaler() 0 -> 0.5390361364389095
1922/3780 0.250 1.814 auto MinMaxScaler() 0 -> 0.5557174977894624
1923/3780 0.250 1.814 0.01 StandardScaler() 0 -> 0.5489823957883867
1924/3780 0.250 1.814 0.01 MinMaxScaler() 0 -> 0.5909901168893422
1925/3780 0.250 1.814 0.03162277660168379 StandardScaler() 0 -> 0.540004210758906
1926/3780 0.250 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5847815135683797
1927/3780 0.250 1.814 0.1 StandardScaler() 0 -> 0.537098326585188
1928/3780 0.250 1.814 0.1 MinMaxScaler() 0 -> 0.5711223684642387
1929/3780 0.250 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5422761138619987
1930/3780 0.250 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5466384342608973
1931/3780 0.250 1.814 1.0 StandardScaler() 0 -> 0.562815066155004
1932/3780 0.250 1.814 1.0 MinMaxScaler() 0 -> 0.538976938161119
1933/3780 0.250 2.302 scale StandardScaler() 0 -> 0.5407594594235735
1934/3780 0.250 2.302 scale MinMaxScaler() 0 -> 0.5380160380022353
1935/3780 0.250 2.302 auto StandardScaler() 0 -> 0.5407594594235742
1936/3780 0.250 2.302 auto MinMaxScaler() 0 -> 0.5531299776904571
1937/3780 0.250 2.302 0.01 StandardScaler() 0 -> 0.5471647958605906
1938/3780 0.250 2.302 0.01 MinMaxScaler() 0 -> 0.5892291387775207
1939/3780 0.250 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5403478705134268
1940/3780 0.250 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5841108895509205
1941/3780 0.250 2.302 0.1 StandardScaler() 0 -> 0.537115596777375
1942/3780 0.250 2.302 0.1 MinMaxScaler() 0 -> 0.5683696210115452
1943/3780 0.250 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5455268871671789
1944/3780 0.250 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5454887554717218
1945/3780 0.250 2.302 1.0 StandardScaler() 0 -> 0.5687847999150032
1946/3780 0.250 2.302 1.0 MinMaxScaler() 0 -> 0.5391529619957481
1947/3780 0.250 2.921 scale StandardScaler() 0 -> 0.5434126338063802
1948/3780 0.250 2.921 scale MinMaxScaler() 0 -> 0.5399585474005704
1949/3780 0.250 2.921 auto StandardScaler() 0 -> 0.5434126338063788
1950/3780 0.250 2.921 auto MinMaxScaler() 0 -> 0.5509197902598993
1951/3780 0.250 2.921 0.01 StandardScaler() 0 -> 0.5458434640883364
1952/3780 0.250 2.921 0.01 MinMaxScaler() 0 -> 0.588295374151353
1953/3780 0.250 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5405030770752236
1954/3780 0.250 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5835354999008978
1955/3780 0.250 2.921 0.1 StandardScaler() 0 -> 0.5377546950373135
1956/3780 0.250 2.921 0.1 MinMaxScaler() 0 -> 0.5658230713626647
1957/3780 0.250 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5496574045932877
1958/3780 0.250 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5447618744176518
1959/3780 0.250 2.921 1.0 StandardScaler() 0 -> 0.5771113478534631
1960/3780 0.250 2.921 1.0 MinMaxScaler() 0 -> 0.5388316649451717
1961/3780 0.250 3.707 scale StandardScaler() 0 -> 0.5451292647506446
1962/3780 0.250 3.707 scale MinMaxScaler() 0 -> 0.5420271304286128
1963/3780 0.250 3.707 auto StandardScaler() 0 -> 0.5451292647506448
1964/3780 0.250 3.707 auto MinMaxScaler() 0 -> 0.5489397503326442
1965/3780 0.250 3.707 0.01 StandardScaler() 0 -> 0.5449173232455001
1966/3780 0.250 3.707 0.01 MinMaxScaler() 0 -> 0.5872090648490492
1967/3780 0.250 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5399611269480452
1968/3780 0.250 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5827330298767431
1969/3780 0.250 3.707 0.1 StandardScaler() 0 -> 0.538939936637755
1970/3780 0.250 3.707 0.1 MinMaxScaler() 0 -> 0.5623269634765835
1971/3780 0.250 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5548647087998213
1972/3780 0.250 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5433341287517666
1973/3780 0.250 3.707 1.0 StandardScaler() 0 -> 0.5862582671117688
1974/3780 0.250 3.707 1.0 MinMaxScaler() 0 -> 0.5382250551712743
1975/3780 0.250 4.703 scale StandardScaler() 0 -> 0.5468637548292224
1976/3780 0.250 4.703 scale MinMaxScaler() 0 -> 0.5440672250644405
1977/3780 0.250 4.703 auto StandardScaler() 0 -> 0.5468637548292228
1978/3780 0.250 4.703 auto MinMaxScaler() 0 -> 0.546824990950726
1979/3780 0.250 4.703 0.01 StandardScaler() 0 -> 0.5442658342921846
1980/3780 0.250 4.703 0.01 MinMaxScaler() 0 -> 0.5864213711874653
1981/3780 0.250 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5395024576133193
1982/3780 0.250 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5816988390497623
1983/3780 0.250 4.703 0.1 StandardScaler() 0 -> 0.5398639255287722
1984/3780 0.250 4.703 0.1 MinMaxScaler() 0 -> 0.5596691520045137
1985/3780 0.250 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5602547491142919
1986/3780 0.250 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5427882131468741
1987/3780 0.250 4.703 1.0 StandardScaler() 0 -> 0.5977144140750036
1988/3780 0.250 4.703 1.0 MinMaxScaler() 0 -> 0.5378122474581996
1989/3780 0.250 5.968 scale StandardScaler() 0 -> 0.5502254852904788
1990/3780 0.250 5.968 scale MinMaxScaler() 0 -> 0.546977201755155
1991/3780 0.250 5.968 auto StandardScaler() 0 -> 0.5502254852904782
1992/3780 0.250 5.968 auto MinMaxScaler() 0 -> 0.5459327587821704
1993/3780 0.250 5.968 0.01 StandardScaler() 0 -> 0.5439185494728623
1994/3780 0.250 5.968 0.01 MinMaxScaler() 0 -> 0.5861073166358782
1995/3780 0.250 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5389841710635912
1996/3780 0.250 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5805587674054643
1997/3780 0.250 5.968 0.1 StandardScaler() 0 -> 0.5410782568066869
1998/3780 0.250 5.968 0.1 MinMaxScaler() 0 -> 0.556923836468525
1999/3780 0.250 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5666218321051892
2000/3780 0.250 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5424919890674413
2001/3780 0.250 5.968 1.0 StandardScaler() 0 -> 0.6098478196070268
2002/3780 0.250 5.968 1.0 MinMaxScaler() 0 -> 0.5373256352120831
2003/3780 0.250 7.574 scale StandardScaler() 0 -> 0.5540547575805518
2004/3780 0.250 7.574 scale MinMaxScaler() 0 -> 0.5499244581159116
2005/3780 0.250 7.574 auto StandardScaler() 0 -> 0.5540547575805537
2006/3780 0.250 7.574 auto MinMaxScaler() 0 -> 0.5449586646369874
2007/3780 0.250 7.574 0.01 StandardScaler() 0 -> 0.5435922571432665
2008/3780 0.250 7.574 0.01 MinMaxScaler() 0 -> 0.5860159824043087
2009/3780 0.250 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5380003298525925
2010/3780 0.250 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5791728193374722
2011/3780 0.250 7.574 0.1 StandardScaler() 0 -> 0.5424824015088281
2012/3780 0.250 7.574 0.1 MinMaxScaler() 0 -> 0.5552638089108631
2013/3780 0.250 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5734772739583064
2014/3780 0.250 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5423026401422563
2015/3780 0.250 7.574 1.0 StandardScaler() 0 -> 0.6255048984216276
2016/3780 0.250 7.574 1.0 MinMaxScaler() 0 -> 0.537169649310072
2017/3780 0.250 9.611 scale StandardScaler() 0 -> 0.5587526946808478
2018/3780 0.250 9.611 scale MinMaxScaler() 0 -> 0.5549214848774415
2019/3780 0.250 9.611 auto StandardScaler() 0 -> 0.5587526946808398
2020/3780 0.250 9.611 auto MinMaxScaler() 0 -> 0.5440375868831584
2021/3780 0.250 9.611 0.01 StandardScaler() 0 -> 0.5434877074958623
2022/3780 0.250 9.611 0.01 MinMaxScaler() 0 -> 0.5859366376888065
2023/3780 0.250 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5377400151645523
2024/3780 0.250 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5774735304431625
2025/3780 0.250 9.611 0.1 StandardScaler() 0 -> 0.5431600819493602
2026/3780 0.250 9.611 0.1 MinMaxScaler() 0 -> 0.5527521759479831
2027/3780 0.250 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5800858248609481
2028/3780 0.250 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5426947972660714
2029/3780 0.250 9.611 1.0 StandardScaler() 0 -> 0.6416358464141255
2030/3780 0.250 9.611 1.0 MinMaxScaler() 0 -> 0.5374656007791979
2031/3780 0.250 12.196 scale StandardScaler() 0 -> 0.5647592938607408
2032/3780 0.250 12.196 scale MinMaxScaler() 0 -> 0.5587259118330692
2033/3780 0.250 12.196 auto StandardScaler() 0 -> 0.5647592938607388
2034/3780 0.250 12.196 auto MinMaxScaler() 0 -> 0.5437338966516195
2035/3780 0.250 12.196 0.01 StandardScaler() 0 -> 0.5436022995558143
2036/3780 0.250 12.196 0.01 MinMaxScaler() 0 -> 0.5856379838792773
2037/3780 0.250 12.196 0.03162277660168379 StandardScaler() 0 -> 0.537827934695947
2038/3780 0.250 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.575363656104657
2039/3780 0.250 12.196 0.1 StandardScaler() 0 -> 0.5442086261676319
2040/3780 0.250 12.196 0.1 MinMaxScaler() 0 -> 0.5504207028430225
2041/3780 0.250 12.196 0.31622776601683794 StandardScaler() 0 -> 0.58732556032245
2042/3780 0.250 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5426313768177319
2043/3780 0.250 12.196 1.0 StandardScaler() 0 -> 0.659793203791264
2044/3780 0.250 12.196 1.0 MinMaxScaler() 0 -> 0.5377475414430247
2045/3780 0.250 15.476 scale StandardScaler() 0 -> 0.5708126669448997
2046/3780 0.250 15.476 scale MinMaxScaler() 0 -> 0.5623172184861297
2047/3780 0.250 15.476 auto StandardScaler() 0 -> 0.5708126669449035
2048/3780 0.250 15.476 auto MinMaxScaler() 0 -> 0.5436319448476703
2049/3780 0.250 15.476 0.01 StandardScaler() 0 -> 0.5434161749637677
2050/3780 0.250 15.476 0.01 MinMaxScaler() 0 -> 0.5852587401705015
2051/3780 0.250 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5378590596084788
2052/3780 0.250 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5729492614038937
2053/3780 0.250 15.476 0.1 StandardScaler() 0 -> 0.5457800423458804
2054/3780 0.250 15.476 0.1 MinMaxScaler() 0 -> 0.5485543228324081
2055/3780 0.250 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5971663957802003
2056/3780 0.250 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5422742917082655
2057/3780 0.250 15.476 1.0 StandardScaler() 0 -> 0.6787597740788921
2058/3780 0.250 15.476 1.0 MinMaxScaler() 0 -> 0.5379115817278662
2059/3780 0.250 19.638 scale StandardScaler() 0 -> 0.577735208390045
2060/3780 0.250 19.638 scale MinMaxScaler() 0 -> 0.5666081955580776
2061/3780 0.250 19.638 auto StandardScaler() 0 -> 0.5777352083900356
2062/3780 0.250 19.638 auto MinMaxScaler() 0 -> 0.5435430456329375
2063/3780 0.250 19.638 0.01 StandardScaler() 0 -> 0.5432133411366117
2064/3780 0.250 19.638 0.01 MinMaxScaler() 0 -> 0.5848798937011729
2065/3780 0.250 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5378426132440365
2066/3780 0.250 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.570143252664106
2067/3780 0.250 19.638 0.1 StandardScaler() 0 -> 0.5471735378380456
2068/3780 0.250 19.638 0.1 MinMaxScaler() 0 -> 0.5472010444093028
2069/3780 0.250 19.638 0.31622776601683794 StandardScaler() 0 -> 0.607318266113866
2070/3780 0.250 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5421068961228633
2071/3780 0.250 19.638 1.0 StandardScaler() 0 -> 0.7004778788411236
2072/3780 0.250 19.638 1.0 MinMaxScaler() 0 -> 0.538183672075114
2073/3780 0.250 24.920 scale StandardScaler() 0 -> 0.585676041736221
2074/3780 0.250 24.920 scale MinMaxScaler() 0 -> 0.5716483409184038
2075/3780 0.250 24.920 auto StandardScaler() 0 -> 0.5856760417362087
2076/3780 0.250 24.920 auto MinMaxScaler() 0 -> 0.543434780138853
2077/3780 0.250 24.920 0.01 StandardScaler() 0 -> 0.543005382537647
2078/3780 0.250 24.920 0.01 MinMaxScaler() 0 -> 0.5844360678943475
2079/3780 0.250 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5380837457335873
2080/3780 0.250 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5675189750145245
2081/3780 0.250 24.920 0.1 StandardScaler() 0 -> 0.5498093321169667
2082/3780 0.250 24.920 0.1 MinMaxScaler() 0 -> 0.5462393187542495
2083/3780 0.250 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6195893327467644
2084/3780 0.250 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5421382010934915
2085/3780 0.250 24.920 1.0 StandardScaler() 0 -> 0.724517259176638
2086/3780 0.250 24.920 1.0 MinMaxScaler() 0 -> 0.5384036423158166
2087/3780 0.250 31.623 scale StandardScaler() 0 -> 0.5935883823117728
2088/3780 0.250 31.623 scale MinMaxScaler() 0 -> 0.576976107915287
2089/3780 0.250 31.623 auto StandardScaler() 0 -> 0.593588382311763
2090/3780 0.250 31.623 auto MinMaxScaler() 0 -> 0.5436106559523989
2091/3780 0.250 31.623 0.01 StandardScaler() 0 -> 0.5427211973348612
2092/3780 0.250 31.623 0.01 MinMaxScaler() 0 -> 0.583803227845561
2093/3780 0.250 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5380880920185614
2094/3780 0.250 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5643218509413676
2095/3780 0.250 31.623 0.1 StandardScaler() 0 -> 0.5531166700029755
2096/3780 0.250 31.623 0.1 MinMaxScaler() 0 -> 0.5453958592860715
2097/3780 0.250 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6336087204998736
2098/3780 0.250 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5421752704991093
2099/3780 0.250 31.623 1.0 StandardScaler() 0 -> 0.751159341402342
2100/3780 0.250 31.623 1.0 MinMaxScaler() 0 -> 0.538495152904899
2101/3780 0.300 0.032 scale StandardScaler() 0 -> 0.5608376301288184
2102/3780 0.300 0.032 scale MinMaxScaler() 0 -> 0.5574309793205027
2103/3780 0.300 0.032 auto StandardScaler() 0 -> 0.5608376301288184
2104/3780 0.300 0.032 auto MinMaxScaler() 0 -> 0.6101176698981142
2105/3780 0.300 0.032 0.01 StandardScaler() 0 -> 0.60794049387996
2106/3780 0.300 0.032 0.01 MinMaxScaler() 0 -> 0.7823076186465361
2107/3780 0.300 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5783316460039797
2108/3780 0.300 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7447888196586749
2109/3780 0.300 0.032 0.1 StandardScaler() 0 -> 0.5601985695395215
2110/3780 0.300 0.032 0.1 MinMaxScaler() 0 -> 0.6566734098618912
2111/3780 0.300 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5671745779269951
2112/3780 0.300 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.59669248317067
2113/3780 0.300 0.032 1.0 StandardScaler() 0 -> 0.6252051846106939
2114/3780 0.300 0.032 1.0 MinMaxScaler() 0 -> 0.5723187665751858
2115/3780 0.300 0.040 scale StandardScaler() 0 -> 0.5568572050034785
2116/3780 0.300 0.040 scale MinMaxScaler() 0 -> 0.5542241391060497
2117/3780 0.300 0.040 auto StandardScaler() 0 -> 0.5568572050034785
2118/3780 0.300 0.040 auto MinMaxScaler() 0 -> 0.6027900617726819
2119/3780 0.300 0.040 0.01 StandardScaler() 0 -> 0.6003528050385256
2120/3780 0.300 0.040 0.01 MinMaxScaler() 0 -> 0.7773434383176533
2121/3780 0.300 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5737832217951249
2122/3780 0.300 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.731103517056131
2123/3780 0.300 0.040 0.1 StandardScaler() 0 -> 0.5563715402980991
2124/3780 0.300 0.040 0.1 MinMaxScaler() 0 -> 0.6339811592112617
2125/3780 0.300 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5621408975678167
2126/3780 0.300 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5905370931064028
2127/3780 0.300 0.040 1.0 StandardScaler() 0 -> 0.609856101870523
2128/3780 0.300 0.040 1.0 MinMaxScaler() 0 -> 0.5687642798424135
2129/3780 0.300 0.051 scale StandardScaler() 0 -> 0.5530053200247075
2130/3780 0.300 0.051 scale MinMaxScaler() 0 -> 0.5517061447709156
2131/3780 0.300 0.051 auto StandardScaler() 0 -> 0.5530053200247075
2132/3780 0.300 0.051 auto MinMaxScaler() 0 -> 0.5959115707390481
2133/3780 0.300 0.051 0.01 StandardScaler() 0 -> 0.5936595419660181
2134/3780 0.300 0.051 0.01 MinMaxScaler() 0 -> 0.7711428054616767
2135/3780 0.300 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5703571498397746
2136/3780 0.300 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7147667971961278
2137/3780 0.300 0.051 0.1 StandardScaler() 0 -> 0.5527741515575221
2138/3780 0.300 0.051 0.1 MinMaxScaler() 0 -> 0.6188266042202838
2139/3780 0.300 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5574309033478975
2140/3780 0.300 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5868885329412369
2141/3780 0.300 0.051 1.0 StandardScaler() 0 -> 0.5954788711636632
2142/3780 0.300 0.051 1.0 MinMaxScaler() 0 -> 0.5656418147221937
2143/3780 0.300 0.065 scale StandardScaler() 0 -> 0.5500861441930178
2144/3780 0.300 0.065 scale MinMaxScaler() 0 -> 0.5490497770465526
2145/3780 0.300 0.065 auto StandardScaler() 0 -> 0.5500861441930178
2146/3780 0.300 0.065 auto MinMaxScaler() 0 -> 0.5909519016290731
2147/3780 0.300 0.065 0.01 StandardScaler() 0 -> 0.5885743717204773
2148/3780 0.300 0.065 0.01 MinMaxScaler() 0 -> 0.7634375511404716
2149/3780 0.300 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5666447300161939
2150/3780 0.300 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6955990977378156
2151/3780 0.300 0.065 0.1 StandardScaler() 0 -> 0.5491697432740229
2152/3780 0.300 0.065 0.1 MinMaxScaler() 0 -> 0.6085874740334405
2153/3780 0.300 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5532048032621784
2154/3780 0.300 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5835517097629415
2155/3780 0.300 0.065 1.0 StandardScaler() 0 -> 0.5843776802376937
2156/3780 0.300 0.065 1.0 MinMaxScaler() 0 -> 0.5625740349248561
2157/3780 0.300 0.082 scale StandardScaler() 0 -> 0.5475308368246908
2158/3780 0.300 0.082 scale MinMaxScaler() 0 -> 0.546547013614812
2159/3780 0.300 0.082 auto StandardScaler() 0 -> 0.5475308368246908
2160/3780 0.300 0.082 auto MinMaxScaler() 0 -> 0.5876205631128105
2161/3780 0.300 0.082 0.01 StandardScaler() 0 -> 0.5853151975943218
2162/3780 0.300 0.082 0.01 MinMaxScaler() 0 -> 0.753906451456476
2163/3780 0.300 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5631074827744779
2164/3780 0.300 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6738067833631242
2165/3780 0.300 0.082 0.1 StandardScaler() 0 -> 0.5465361498889812
2166/3780 0.300 0.082 0.1 MinMaxScaler() 0 -> 0.6018476889690562
2167/3780 0.300 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5497495296508031
2168/3780 0.300 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5807050733955846
2169/3780 0.300 0.082 1.0 StandardScaler() 0 -> 0.5744286772328543
2170/3780 0.300 0.082 1.0 MinMaxScaler() 0 -> 0.5595298966969996
2171/3780 0.300 0.104 scale StandardScaler() 0 -> 0.5451363688141946
2172/3780 0.300 0.104 scale MinMaxScaler() 0 -> 0.5444416033087278
2173/3780 0.300 0.104 auto StandardScaler() 0 -> 0.5451363688141946
2174/3780 0.300 0.104 auto MinMaxScaler() 0 -> 0.5849697025476409
2175/3780 0.300 0.104 0.01 StandardScaler() 0 -> 0.5823179793544454
2176/3780 0.300 0.104 0.01 MinMaxScaler() 0 -> 0.742229297612195
2177/3780 0.300 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5597443267835361
2178/3780 0.300 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6505126312504657
2179/3780 0.300 0.104 0.1 StandardScaler() 0 -> 0.5449560488430624
2180/3780 0.300 0.104 0.1 MinMaxScaler() 0 -> 0.5953835355512281
2181/3780 0.300 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5470400118056061
2182/3780 0.300 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5782189654882489
2183/3780 0.300 0.104 1.0 StandardScaler() 0 -> 0.5662531277279478
2184/3780 0.300 0.104 1.0 MinMaxScaler() 0 -> 0.556129338306388
2185/3780 0.300 0.132 scale StandardScaler() 0 -> 0.5434094284774228
2186/3780 0.300 0.132 scale MinMaxScaler() 0 -> 0.54267857449125
2187/3780 0.300 0.132 auto StandardScaler() 0 -> 0.5434094284774226
2188/3780 0.300 0.132 auto MinMaxScaler() 0 -> 0.582432723016561
2189/3780 0.300 0.132 0.01 StandardScaler() 0 -> 0.5794347251981351
2190/3780 0.300 0.132 0.01 MinMaxScaler() 0 -> 0.7280814056557045
2191/3780 0.300 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5563584401175022
2192/3780 0.300 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6290060671153445
2193/3780 0.300 0.132 0.1 StandardScaler() 0 -> 0.5436633727713157
2194/3780 0.300 0.132 0.1 MinMaxScaler() 0 -> 0.5917340266402383
2195/3780 0.300 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5447339200895561
2196/3780 0.300 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5755071922109686
2197/3780 0.300 0.132 1.0 StandardScaler() 0 -> 0.5592277194397405
2198/3780 0.300 0.132 1.0 MinMaxScaler() 0 -> 0.5532828704455769
2199/3780 0.300 0.168 scale StandardScaler() 0 -> 0.5419231475192371
2200/3780 0.300 0.168 scale MinMaxScaler() 0 -> 0.5410503697340023
2201/3780 0.300 0.168 auto StandardScaler() 0 -> 0.541923147519237
2202/3780 0.300 0.168 auto MinMaxScaler() 0 -> 0.5802820499856568
2203/3780 0.300 0.168 0.01 StandardScaler() 0 -> 0.5767780818727148
2204/3780 0.300 0.168 0.01 MinMaxScaler() 0 -> 0.7111893137840971
2205/3780 0.300 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5535332471030512
2206/3780 0.300 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6156830312552392
2207/3780 0.300 0.168 0.1 StandardScaler() 0 -> 0.5419945571298104
2208/3780 0.300 0.168 0.1 MinMaxScaler() 0 -> 0.5887706666981657
2209/3780 0.300 0.168 0.31622776601683794 StandardScaler() 0 -> 0.542199380680423
2210/3780 0.300 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.573333782030519
2211/3780 0.300 0.168 1.0 StandardScaler() 0 -> 0.55417418077668
2212/3780 0.300 0.168 1.0 MinMaxScaler() 0 -> 0.5505397125238883
2213/3780 0.300 0.213 scale StandardScaler() 0 -> 0.5399513759175609
2214/3780 0.300 0.213 scale MinMaxScaler() 0 -> 0.5398389916205469
2215/3780 0.300 0.213 auto StandardScaler() 0 -> 0.5399513759175608
2216/3780 0.300 0.213 auto MinMaxScaler() 0 -> 0.5783650978589248
2217/3780 0.300 0.213 0.01 StandardScaler() 0 -> 0.5744841636088679
2218/3780 0.300 0.213 0.01 MinMaxScaler() 0 -> 0.6914138230624151
2219/3780 0.300 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5514609882449953
2220/3780 0.300 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6069000543439179
2221/3780 0.300 0.213 0.1 StandardScaler() 0 -> 0.5406011933705457
2222/3780 0.300 0.213 0.1 MinMaxScaler() 0 -> 0.5861853783333354
2223/3780 0.300 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5401143890691756
2224/3780 0.300 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5710723938132933
2225/3780 0.300 0.213 1.0 StandardScaler() 0 -> 0.5490850443574739
2226/3780 0.300 0.213 1.0 MinMaxScaler() 0 -> 0.548366817601929
2227/3780 0.300 0.270 scale StandardScaler() 0 -> 0.5391537961358572
2228/3780 0.300 0.270 scale MinMaxScaler() 0 -> 0.5385091735998232
2229/3780 0.300 0.270 auto StandardScaler() 0 -> 0.5391537961358571
2230/3780 0.300 0.270 auto MinMaxScaler() 0 -> 0.5763650299540197
2231/3780 0.300 0.270 0.01 StandardScaler() 0 -> 0.5718171382923617
2232/3780 0.300 0.270 0.01 MinMaxScaler() 0 -> 0.6691578158109882
2233/3780 0.300 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5492081702712152
2234/3780 0.300 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6004955817975121
2235/3780 0.300 0.270 0.1 StandardScaler() 0 -> 0.5400025258817165
2236/3780 0.300 0.270 0.1 MinMaxScaler() 0 -> 0.5845040101474099
2237/3780 0.300 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5387511493262012
2238/3780 0.300 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5683306114754655
2239/3780 0.300 0.270 1.0 StandardScaler() 0 -> 0.5448563815941313
2240/3780 0.300 0.270 1.0 MinMaxScaler() 0 -> 0.5458016590994781
2241/3780 0.300 0.342 scale StandardScaler() 0 -> 0.538015729679174
2242/3780 0.300 0.342 scale MinMaxScaler() 0 -> 0.5376094537218433
2243/3780 0.300 0.342 auto StandardScaler() 0 -> 0.5380157296791737
2244/3780 0.300 0.342 auto MinMaxScaler() 0 -> 0.5743745451073718
2245/3780 0.300 0.342 0.01 StandardScaler() 0 -> 0.5691327819768465
2246/3780 0.300 0.342 0.01 MinMaxScaler() 0 -> 0.6457020413021355
2247/3780 0.300 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5465156758677154
2248/3780 0.300 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5950334581596612
2249/3780 0.300 0.342 0.1 StandardScaler() 0 -> 0.5391321805683115
2250/3780 0.300 0.342 0.1 MinMaxScaler() 0 -> 0.5827637930512876
2251/3780 0.300 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5374000979793279
2252/3780 0.300 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5653707063245051
2253/3780 0.300 0.342 1.0 StandardScaler() 0 -> 0.5419029015014697
2254/3780 0.300 0.342 1.0 MinMaxScaler() 0 -> 0.5442662443809447
2255/3780 0.300 0.434 scale StandardScaler() 0 -> 0.5371338351748419
2256/3780 0.300 0.434 scale MinMaxScaler() 0 -> 0.5370215712038967
2257/3780 0.300 0.434 auto StandardScaler() 0 -> 0.5371338351748419
2258/3780 0.300 0.434 auto MinMaxScaler() 0 -> 0.5721252394300821
2259/3780 0.300 0.434 0.01 StandardScaler() 0 -> 0.5663904559137828
2260/3780 0.300 0.434 0.01 MinMaxScaler() 0 -> 0.6256174557207805
2261/3780 0.300 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5447239881983409
2262/3780 0.300 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5920425665624379
2263/3780 0.300 0.434 0.1 StandardScaler() 0 -> 0.5380051807565451
2264/3780 0.300 0.434 0.1 MinMaxScaler() 0 -> 0.5813834050587157
2265/3780 0.300 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5365510685872235
2266/3780 0.300 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5624058672988669
2267/3780 0.300 0.434 1.0 StandardScaler() 0 -> 0.5402715845489299
2268/3780 0.300 0.434 1.0 MinMaxScaler() 0 -> 0.5427032845248013
2269/3780 0.300 0.551 scale StandardScaler() 0 -> 0.5365708958732462
2270/3780 0.300 0.551 scale MinMaxScaler() 0 -> 0.536378369791056
2271/3780 0.300 0.551 auto StandardScaler() 0 -> 0.536570895873246
2272/3780 0.300 0.551 auto MinMaxScaler() 0 -> 0.5696545209062488
2273/3780 0.300 0.551 0.01 StandardScaler() 0 -> 0.563586765048798
2274/3780 0.300 0.551 0.01 MinMaxScaler() 0 -> 0.6136419510100996
2275/3780 0.300 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5436146729543637
2276/3780 0.300 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5892612098298907
2277/3780 0.300 0.551 0.1 StandardScaler() 0 -> 0.5370311257992375
2278/3780 0.300 0.551 0.1 MinMaxScaler() 0 -> 0.5802137870427647
2279/3780 0.300 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5353815886930052
2280/3780 0.300 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5599526414335553
2281/3780 0.300 0.551 1.0 StandardScaler() 0 -> 0.5396544510596861
2282/3780 0.300 0.551 1.0 MinMaxScaler() 0 -> 0.5412477190375364
2283/3780 0.300 0.700 scale StandardScaler() 0 -> 0.5359433645899623
2284/3780 0.300 0.700 scale MinMaxScaler() 0 -> 0.5355887980866195
2285/3780 0.300 0.700 auto StandardScaler() 0 -> 0.5359433645899622
2286/3780 0.300 0.700 auto MinMaxScaler() 0 -> 0.5670527113108754
2287/3780 0.300 0.700 0.01 StandardScaler() 0 -> 0.5610884811532477
2288/3780 0.300 0.700 0.01 MinMaxScaler() 0 -> 0.6056594249661132
2289/3780 0.300 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5427834542451828
2290/3780 0.300 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5871713703047234
2291/3780 0.300 0.700 0.1 StandardScaler() 0 -> 0.5361799628959348
2292/3780 0.300 0.700 0.1 MinMaxScaler() 0 -> 0.5788403318746592
2293/3780 0.300 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5352072292593694
2294/3780 0.300 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5579450123268485
2295/3780 0.300 0.700 1.0 StandardScaler() 0 -> 0.5412348629041852
2296/3780 0.300 0.700 1.0 MinMaxScaler() 0 -> 0.5406545280529165
2297/3780 0.300 0.888 scale StandardScaler() 0 -> 0.5359725471202629
2298/3780 0.300 0.888 scale MinMaxScaler() 0 -> 0.5348386965614967
2299/3780 0.300 0.888 auto StandardScaler() 0 -> 0.535972547120263
2300/3780 0.300 0.888 auto MinMaxScaler() 0 -> 0.5644037952911809
2301/3780 0.300 0.888 0.01 StandardScaler() 0 -> 0.55882083396299
2302/3780 0.300 0.888 0.01 MinMaxScaler() 0 -> 0.5993732805841366
2303/3780 0.300 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5419742817675764
2304/3780 0.300 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5861928588708615
2305/3780 0.300 0.888 0.1 StandardScaler() 0 -> 0.53590165629728
2306/3780 0.300 0.888 0.1 MinMaxScaler() 0 -> 0.5776120493989114
2307/3780 0.300 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5361523493041536
2308/3780 0.300 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.555147190701215
2309/3780 0.300 0.888 1.0 StandardScaler() 0 -> 0.5437786105798331
2310/3780 0.300 0.888 1.0 MinMaxScaler() 0 -> 0.5398657681436624
2311/3780 0.300 1.126 scale StandardScaler() 0 -> 0.5363010062058086
2312/3780 0.300 1.126 scale MinMaxScaler() 0 -> 0.5348264456085229
2313/3780 0.300 1.126 auto StandardScaler() 0 -> 0.5363010062058077
2314/3780 0.300 1.126 auto MinMaxScaler() 0 -> 0.5614745944215537
2315/3780 0.300 1.126 0.01 StandardScaler() 0 -> 0.5558623594913584
2316/3780 0.300 1.126 0.01 MinMaxScaler() 0 -> 0.5944436150797286
2317/3780 0.300 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5412427264036227
2318/3780 0.300 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5851844665799667
2319/3780 0.300 1.126 0.1 StandardScaler() 0 -> 0.5361254555472335
2320/3780 0.300 1.126 0.1 MinMaxScaler() 0 -> 0.5758605710374173
2321/3780 0.300 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5381044720206659
2322/3780 0.300 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5528854032873607
2323/3780 0.300 1.126 1.0 StandardScaler() 0 -> 0.5473842264982315
2324/3780 0.300 1.126 1.0 MinMaxScaler() 0 -> 0.5393256959583658
2325/3780 0.300 1.429 scale StandardScaler() 0 -> 0.5367546359368576
2326/3780 0.300 1.429 scale MinMaxScaler() 0 -> 0.535025556158603
2327/3780 0.300 1.429 auto StandardScaler() 0 -> 0.5367546359368569
2328/3780 0.300 1.429 auto MinMaxScaler() 0 -> 0.5596017763039761
2329/3780 0.300 1.429 0.01 StandardScaler() 0 -> 0.5530348617099087
2330/3780 0.300 1.429 0.01 MinMaxScaler() 0 -> 0.591926591981908
2331/3780 0.300 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5404970227200687
2332/3780 0.300 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5840560362651943
2333/3780 0.300 1.429 0.1 StandardScaler() 0 -> 0.5359972116366937
2334/3780 0.300 1.429 0.1 MinMaxScaler() 0 -> 0.5737840190280226
2335/3780 0.300 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5402215064238953
2336/3780 0.300 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.550525109503558
2337/3780 0.300 1.429 1.0 StandardScaler() 0 -> 0.5519205206259022
2338/3780 0.300 1.429 1.0 MinMaxScaler() 0 -> 0.5383705148595843
2339/3780 0.300 1.814 scale StandardScaler() 0 -> 0.5377592675101556
2340/3780 0.300 1.814 scale MinMaxScaler() 0 -> 0.5355850900110869
2341/3780 0.300 1.814 auto StandardScaler() 0 -> 0.5377592675101561
2342/3780 0.300 1.814 auto MinMaxScaler() 0 -> 0.5572903037327381
2343/3780 0.300 1.814 0.01 StandardScaler() 0 -> 0.5506796426109201
2344/3780 0.300 1.814 0.01 MinMaxScaler() 0 -> 0.5892605404295067
2345/3780 0.300 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5396978765814225
2346/3780 0.300 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5835858990408067
2347/3780 0.300 1.814 0.1 StandardScaler() 0 -> 0.5360197370231434
2348/3780 0.300 1.814 0.1 MinMaxScaler() 0 -> 0.5713625096227872
2349/3780 0.300 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5421538922623877
2350/3780 0.300 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5484236321402939
2351/3780 0.300 1.814 1.0 StandardScaler() 0 -> 0.5570954125402067
2352/3780 0.300 1.814 1.0 MinMaxScaler() 0 -> 0.5376940639865551
2353/3780 0.300 2.302 scale StandardScaler() 0 -> 0.5395445238706884
2354/3780 0.300 2.302 scale MinMaxScaler() 0 -> 0.5367447051508706
2355/3780 0.300 2.302 auto StandardScaler() 0 -> 0.539544523870689
2356/3780 0.300 2.302 auto MinMaxScaler() 0 -> 0.5545683192842406
2357/3780 0.300 2.302 0.01 StandardScaler() 0 -> 0.5488029152363685
2358/3780 0.300 2.302 0.01 MinMaxScaler() 0 -> 0.5875202955762789
2359/3780 0.300 2.302 0.03162277660168379 StandardScaler() 0 -> 0.539232883642354
2360/3780 0.300 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5832685778669482
2361/3780 0.300 2.302 0.1 StandardScaler() 0 -> 0.5372736758186726
2362/3780 0.300 2.302 0.1 MinMaxScaler() 0 -> 0.5690297754851837
2363/3780 0.300 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5451727983837876
2364/3780 0.300 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5470453489236213
2365/3780 0.300 2.302 1.0 StandardScaler() 0 -> 0.5623050196058297
2366/3780 0.300 2.302 1.0 MinMaxScaler() 0 -> 0.5375237351937137
2367/3780 0.300 2.921 scale StandardScaler() 0 -> 0.5418249188296489
2368/3780 0.300 2.921 scale MinMaxScaler() 0 -> 0.538703830937008
2369/3780 0.300 2.921 auto StandardScaler() 0 -> 0.5418249188296471
2370/3780 0.300 2.921 auto MinMaxScaler() 0 -> 0.5525467774619931
2371/3780 0.300 2.921 0.01 StandardScaler() 0 -> 0.5474807478437316
2372/3780 0.300 2.921 0.01 MinMaxScaler() 0 -> 0.5865868570104485
2373/3780 0.300 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5387791304140812
2374/3780 0.300 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5825595315218717
2375/3780 0.300 2.921 0.1 StandardScaler() 0 -> 0.5379247923064122
2376/3780 0.300 2.921 0.1 MinMaxScaler() 0 -> 0.5662890964476897
2377/3780 0.300 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5495324566137921
2378/3780 0.300 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5459339931455163
2379/3780 0.300 2.921 1.0 StandardScaler() 0 -> 0.568481370134252
2380/3780 0.300 2.921 1.0 MinMaxScaler() 0 -> 0.5372126713241411
2381/3780 0.300 3.707 scale StandardScaler() 0 -> 0.5436092969644933
2382/3780 0.300 3.707 scale MinMaxScaler() 0 -> 0.5409964079779896
2383/3780 0.300 3.707 auto StandardScaler() 0 -> 0.543609296964494
2384/3780 0.300 3.707 auto MinMaxScaler() 0 -> 0.5505679067567172
2385/3780 0.300 3.707 0.01 StandardScaler() 0 -> 0.5464648994566829
2386/3780 0.300 3.707 0.01 MinMaxScaler() 0 -> 0.5856188281613511
2387/3780 0.300 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5386795609820146
2388/3780 0.300 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5818365235978121
2389/3780 0.300 3.707 0.1 StandardScaler() 0 -> 0.5387333707007572
2390/3780 0.300 3.707 0.1 MinMaxScaler() 0 -> 0.5635084807504982
2391/3780 0.300 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5545916949381074
2392/3780 0.300 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5449410085258801
2393/3780 0.300 3.707 1.0 StandardScaler() 0 -> 0.5772111015410616
2394/3780 0.300 3.707 1.0 MinMaxScaler() 0 -> 0.5369658422606974
2395/3780 0.300 4.703 scale StandardScaler() 0 -> 0.545969052871001
2396/3780 0.300 4.703 scale MinMaxScaler() 0 -> 0.5430717928473024
2397/3780 0.300 4.703 auto StandardScaler() 0 -> 0.5459690528710023
2398/3780 0.300 4.703 auto MinMaxScaler() 0 -> 0.5486633141312544
2399/3780 0.300 4.703 0.01 StandardScaler() 0 -> 0.5455621085015742
2400/3780 0.300 4.703 0.01 MinMaxScaler() 0 -> 0.5852914802944164
2401/3780 0.300 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5382185724826536
2402/3780 0.300 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5809970225010866
2403/3780 0.300 4.703 0.1 StandardScaler() 0 -> 0.540020898055989
2404/3780 0.300 4.703 0.1 MinMaxScaler() 0 -> 0.5607528713624568
2405/3780 0.300 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5584537652549885
2406/3780 0.300 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5441574297501909
2407/3780 0.300 4.703 1.0 StandardScaler() 0 -> 0.5894511960490137
2408/3780 0.300 4.703 1.0 MinMaxScaler() 0 -> 0.5371307650042293
2409/3780 0.300 5.968 scale StandardScaler() 0 -> 0.5494514180898615
2410/3780 0.300 5.968 scale MinMaxScaler() 0 -> 0.5451769260628301
2411/3780 0.300 5.968 auto StandardScaler() 0 -> 0.5494514180898609
2412/3780 0.300 5.968 auto MinMaxScaler() 0 -> 0.547329407654152
2413/3780 0.300 5.968 0.01 StandardScaler() 0 -> 0.5449728578397858
2414/3780 0.300 5.968 0.01 MinMaxScaler() 0 -> 0.5850277071232318
2415/3780 0.300 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5379912273083831
2416/3780 0.300 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5801127187617521
2417/3780 0.300 5.968 0.1 StandardScaler() 0 -> 0.5415448140292071
2418/3780 0.300 5.968 0.1 MinMaxScaler() 0 -> 0.5589986680051807
2419/3780 0.300 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5647865020362658
2420/3780 0.300 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5433241745469658
2421/3780 0.300 5.968 1.0 StandardScaler() 0 -> 0.6023702186594022
2422/3780 0.300 5.968 1.0 MinMaxScaler() 0 -> 0.5370828906211295
2423/3780 0.300 7.574 scale StandardScaler() 0 -> 0.5534836355120363
2424/3780 0.300 7.574 scale MinMaxScaler() 0 -> 0.5489940094696965
2425/3780 0.300 7.574 auto StandardScaler() 0 -> 0.5534836355120335
2426/3780 0.300 7.574 auto MinMaxScaler() 0 -> 0.5461496085363128
2427/3780 0.300 7.574 0.01 StandardScaler() 0 -> 0.544768470403903
2428/3780 0.300 7.574 0.01 MinMaxScaler() 0 -> 0.585118714040194
2429/3780 0.300 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5374206899006607
2430/3780 0.300 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5788128937782364
2431/3780 0.300 7.574 0.1 StandardScaler() 0 -> 0.5427195893230022
2432/3780 0.300 7.574 0.1 MinMaxScaler() 0 -> 0.556575005213941
2433/3780 0.300 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5714851288404942
2434/3780 0.300 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5431335615673333
2435/3780 0.300 7.574 1.0 StandardScaler() 0 -> 0.6179674604069646
2436/3780 0.300 7.574 1.0 MinMaxScaler() 0 -> 0.5367991185118465
2437/3780 0.300 9.611 scale StandardScaler() 0 -> 0.5580087910190367
2438/3780 0.300 9.611 scale MinMaxScaler() 0 -> 0.5533263344482352
2439/3780 0.300 9.611 auto StandardScaler() 0 -> 0.558008791019038
2440/3780 0.300 9.611 auto MinMaxScaler() 0 -> 0.5450352349507424
2441/3780 0.300 9.611 0.01 StandardScaler() 0 -> 0.544168319884144
2442/3780 0.300 9.611 0.01 MinMaxScaler() 0 -> 0.5846253818876223
2443/3780 0.300 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5369122716765081
2444/3780 0.300 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5770110597809303
2445/3780 0.300 9.611 0.1 StandardScaler() 0 -> 0.5435763914561286
2446/3780 0.300 9.611 0.1 MinMaxScaler() 0 -> 0.5541338919612385
2447/3780 0.300 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5772421966917355
2448/3780 0.300 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5429948484281119
2449/3780 0.300 9.611 1.0 StandardScaler() 0 -> 0.6330321902847653
2450/3780 0.300 9.611 1.0 MinMaxScaler() 0 -> 0.5370177230415076
2451/3780 0.300 12.196 scale StandardScaler() 0 -> 0.5635789987699518
2452/3780 0.300 12.196 scale MinMaxScaler() 0 -> 0.5574832427488495
2453/3780 0.300 12.196 auto StandardScaler() 0 -> 0.563578998769954
2454/3780 0.300 12.196 auto MinMaxScaler() 0 -> 0.5442171337654184
2455/3780 0.300 12.196 0.01 StandardScaler() 0 -> 0.5440785785097875
2456/3780 0.300 12.196 0.01 MinMaxScaler() 0 -> 0.584329966495481
2457/3780 0.300 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5364348405790701
2458/3780 0.300 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5750465393444689
2459/3780 0.300 12.196 0.1 StandardScaler() 0 -> 0.5448350899072717
2460/3780 0.300 12.196 0.1 MinMaxScaler() 0 -> 0.5523237796229893
2461/3780 0.300 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5845188487291968
2462/3780 0.300 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5425624348050341
2463/3780 0.300 12.196 1.0 StandardScaler() 0 -> 0.6478850751753962
2464/3780 0.300 12.196 1.0 MinMaxScaler() 0 -> 0.5368795880164453
2465/3780 0.300 15.476 scale StandardScaler() 0 -> 0.5696427614034879
2466/3780 0.300 15.476 scale MinMaxScaler() 0 -> 0.5616701822058237
2467/3780 0.300 15.476 auto StandardScaler() 0 -> 0.5696427614034919
2468/3780 0.300 15.476 auto MinMaxScaler() 0 -> 0.54395751374397
2469/3780 0.300 15.476 0.01 StandardScaler() 0 -> 0.54348569364411
2470/3780 0.300 15.476 0.01 MinMaxScaler() 0 -> 0.5839684763823
2471/3780 0.300 15.476 0.03162277660168379 StandardScaler() 0 -> 0.536579699990127
2472/3780 0.300 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5730085594617789
2473/3780 0.300 15.476 0.1 StandardScaler() 0 -> 0.5460623941243071
2474/3780 0.300 15.476 0.1 MinMaxScaler() 0 -> 0.5500567137317994
2475/3780 0.300 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5919177135655157
2476/3780 0.300 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5418303530119012
2477/3780 0.300 15.476 1.0 StandardScaler() 0 -> 0.664051850469379
2478/3780 0.300 15.476 1.0 MinMaxScaler() 0 -> 0.5368809957641648
2479/3780 0.300 19.638 scale StandardScaler() 0 -> 0.5768646937441136
2480/3780 0.300 19.638 scale MinMaxScaler() 0 -> 0.5666155859953675
2481/3780 0.300 19.638 auto StandardScaler() 0 -> 0.5768646937441
2482/3780 0.300 19.638 auto MinMaxScaler() 0 -> 0.5438726247752507
2483/3780 0.300 19.638 0.01 StandardScaler() 0 -> 0.5432482240359837
2484/3780 0.300 19.638 0.01 MinMaxScaler() 0 -> 0.5836483405391317
2485/3780 0.300 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5367859659278009
2486/3780 0.300 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5704451401010902
2487/3780 0.300 19.638 0.1 StandardScaler() 0 -> 0.5469220976658308
2488/3780 0.300 19.638 0.1 MinMaxScaler() 0 -> 0.5487590922143673
2489/3780 0.300 19.638 0.31622776601683794 StandardScaler() 0 -> 0.6013118547415434
2490/3780 0.300 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5413847656177158
2491/3780 0.300 19.638 1.0 StandardScaler() 0 -> 0.6835887585165272
2492/3780 0.300 19.638 1.0 MinMaxScaler() 0 -> 0.5371456353096723
2493/3780 0.300 24.920 scale StandardScaler() 0 -> 0.5833320352406667
2494/3780 0.300 24.920 scale MinMaxScaler() 0 -> 0.5715202544171808
2495/3780 0.300 24.920 auto StandardScaler() 0 -> 0.5833320352406651
2496/3780 0.300 24.920 auto MinMaxScaler() 0 -> 0.5436872633843243
2497/3780 0.300 24.920 0.01 StandardScaler() 0 -> 0.5427946303695975
2498/3780 0.300 24.920 0.01 MinMaxScaler() 0 -> 0.5829912989163263
2499/3780 0.300 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5374283467470452
2500/3780 0.300 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.567741990213006
2501/3780 0.300 24.920 0.1 StandardScaler() 0 -> 0.547709752665252
2502/3780 0.300 24.920 0.1 MinMaxScaler() 0 -> 0.5472890667033762
2503/3780 0.300 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6150134900856861
2504/3780 0.300 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.540934566140429
2505/3780 0.300 24.920 1.0 StandardScaler() 0 -> 0.7054221283620211
2506/3780 0.300 24.920 1.0 MinMaxScaler() 0 -> 0.5373889669233254
2507/3780 0.300 31.623 scale StandardScaler() 0 -> 0.5906694981153491
2508/3780 0.300 31.623 scale MinMaxScaler() 0 -> 0.5775552772505135
2509/3780 0.300 31.623 auto StandardScaler() 0 -> 0.5906694981153433
2510/3780 0.300 31.623 auto MinMaxScaler() 0 -> 0.5432954374205897
2511/3780 0.300 31.623 0.01 StandardScaler() 0 -> 0.5418439852496508
2512/3780 0.300 31.623 0.01 MinMaxScaler() 0 -> 0.5822834466104364
2513/3780 0.300 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5376006627341188
2514/3780 0.300 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5650739024154742
2515/3780 0.300 31.623 0.1 StandardScaler() 0 -> 0.5503183951058775
2516/3780 0.300 31.623 0.1 MinMaxScaler() 0 -> 0.5463773442123085
2517/3780 0.300 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6291918497907404
2518/3780 0.300 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5402890542236657
2519/3780 0.300 31.623 1.0 StandardScaler() 0 -> 0.7287347693888159
2520/3780 0.300 31.623 1.0 MinMaxScaler() 0 -> 0.537138524299432
2521/3780 0.350 0.032 scale StandardScaler() 0 -> 0.5625197398564179
2522/3780 0.350 0.032 scale MinMaxScaler() 0 -> 0.5601321177874937
2523/3780 0.350 0.032 auto StandardScaler() 0 -> 0.5625197398564179
2524/3780 0.350 0.032 auto MinMaxScaler() 0 -> 0.6072091062235948
2525/3780 0.350 0.032 0.01 StandardScaler() 0 -> 0.6052259917896475
2526/3780 0.350 0.032 0.01 MinMaxScaler() 0 -> 0.8047389209521794
2527/3780 0.350 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5781022564606279
2528/3780 0.350 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7643217795049521
2529/3780 0.350 0.032 0.1 StandardScaler() 0 -> 0.5623628323958368
2530/3780 0.350 0.032 0.1 MinMaxScaler() 0 -> 0.6672910381487996
2531/3780 0.350 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5685753442464707
2532/3780 0.350 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5953682805158079
2533/3780 0.350 0.032 1.0 StandardScaler() 0 -> 0.6304177782112409
2534/3780 0.350 0.032 1.0 MinMaxScaler() 0 -> 0.573918063677833
2535/3780 0.350 0.040 scale StandardScaler() 0 -> 0.5590391303386079
2536/3780 0.350 0.040 scale MinMaxScaler() 0 -> 0.5574175132124143
2537/3780 0.350 0.040 auto StandardScaler() 0 -> 0.5590391303386077
2538/3780 0.350 0.040 auto MinMaxScaler() 0 -> 0.5995309806094867
2539/3780 0.350 0.040 0.01 StandardScaler() 0 -> 0.5971715943413348
2540/3780 0.350 0.040 0.01 MinMaxScaler() 0 -> 0.7994092630561166
2541/3780 0.350 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5747850822696752
2542/3780 0.350 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7495476692561267
2543/3780 0.350 0.040 0.1 StandardScaler() 0 -> 0.5584022317860767
2544/3780 0.350 0.040 0.1 MinMaxScaler() 0 -> 0.6403414637536036
2545/3780 0.350 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5634907357263731
2546/3780 0.350 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5896927858816698
2547/3780 0.350 0.040 1.0 StandardScaler() 0 -> 0.6124502493157072
2548/3780 0.350 0.040 1.0 MinMaxScaler() 0 -> 0.5710408033449146
2549/3780 0.350 0.051 scale StandardScaler() 0 -> 0.5554470928878064
2550/3780 0.350 0.051 scale MinMaxScaler() 0 -> 0.5551811547971242
2551/3780 0.350 0.051 auto StandardScaler() 0 -> 0.5554470928878062
2552/3780 0.350 0.051 auto MinMaxScaler() 0 -> 0.594718074706276
2553/3780 0.350 0.051 0.01 StandardScaler() 0 -> 0.5926271075355551
2554/3780 0.350 0.051 0.01 MinMaxScaler() 0 -> 0.7927494502468958
2555/3780 0.350 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5716372496995725
2556/3780 0.350 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.731683304475431
2557/3780 0.350 0.051 0.1 StandardScaler() 0 -> 0.5554409323962061
2558/3780 0.350 0.051 0.1 MinMaxScaler() 0 -> 0.6179556801363411
2559/3780 0.350 0.051 0.31622776601683794 StandardScaler() 0 -> 0.559470658949022
2560/3780 0.350 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5860359624245494
2561/3780 0.350 0.051 1.0 StandardScaler() 0 -> 0.5977669047240332
2562/3780 0.350 0.051 1.0 MinMaxScaler() 0 -> 0.5679564471434564
2563/3780 0.350 0.065 scale StandardScaler() 0 -> 0.5526050550262601
2564/3780 0.350 0.065 scale MinMaxScaler() 0 -> 0.5524874024402907
2565/3780 0.350 0.065 auto StandardScaler() 0 -> 0.5526050550262602
2566/3780 0.350 0.065 auto MinMaxScaler() 0 -> 0.5900045635778478
2567/3780 0.350 0.065 0.01 StandardScaler() 0 -> 0.5875229062463362
2568/3780 0.350 0.065 0.01 MinMaxScaler() 0 -> 0.7844469399636865
2569/3780 0.350 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5686756836974838
2570/3780 0.350 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.7106668626473877
2571/3780 0.350 0.065 0.1 StandardScaler() 0 -> 0.5527101094986584
2572/3780 0.350 0.065 0.1 MinMaxScaler() 0 -> 0.6058625506183274
2573/3780 0.350 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5557786150469619
2574/3780 0.350 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5832756449622691
2575/3780 0.350 0.065 1.0 StandardScaler() 0 -> 0.5857201025202677
2576/3780 0.350 0.065 1.0 MinMaxScaler() 0 -> 0.5650089399222481
2577/3780 0.350 0.082 scale StandardScaler() 0 -> 0.5503004827252335
2578/3780 0.350 0.082 scale MinMaxScaler() 0 -> 0.5506247990171401
2579/3780 0.350 0.082 auto StandardScaler() 0 -> 0.5503004827252332
2580/3780 0.350 0.082 auto MinMaxScaler() 0 -> 0.5865349290186445
2581/3780 0.350 0.082 0.01 StandardScaler() 0 -> 0.5842907319830891
2582/3780 0.350 0.082 0.01 MinMaxScaler() 0 -> 0.7741248250347542
2583/3780 0.350 0.082 0.03162277660168379 StandardScaler() 0 -> 0.565669751793422
2584/3780 0.350 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6865349488054323
2585/3780 0.350 0.082 0.1 StandardScaler() 0 -> 0.5501902888927778
2586/3780 0.350 0.082 0.1 MinMaxScaler() 0 -> 0.5989342263574611
2587/3780 0.350 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5518711062546071
2588/3780 0.350 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5810000326326407
2589/3780 0.350 0.082 1.0 StandardScaler() 0 -> 0.5756546815276701
2590/3780 0.350 0.082 1.0 MinMaxScaler() 0 -> 0.5621149566392419
2591/3780 0.350 0.104 scale StandardScaler() 0 -> 0.5483613885330857
2592/3780 0.350 0.104 scale MinMaxScaler() 0 -> 0.5485100688329484
2593/3780 0.350 0.104 auto StandardScaler() 0 -> 0.5483613885330857
2594/3780 0.350 0.104 auto MinMaxScaler() 0 -> 0.5843209898045197
2595/3780 0.350 0.104 0.01 StandardScaler() 0 -> 0.5817720760543706
2596/3780 0.350 0.104 0.01 MinMaxScaler() 0 -> 0.7615483659925433
2597/3780 0.350 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5622805460272018
2598/3780 0.350 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6599051733815054
2599/3780 0.350 0.104 0.1 StandardScaler() 0 -> 0.5484648944292573
2600/3780 0.350 0.104 0.1 MinMaxScaler() 0 -> 0.5942803363927661
2601/3780 0.350 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5489144445055433
2602/3780 0.350 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5789584140021362
2603/3780 0.350 0.104 1.0 StandardScaler() 0 -> 0.5674832747254275
2604/3780 0.350 0.104 1.0 MinMaxScaler() 0 -> 0.5594148297570444
2605/3780 0.350 0.132 scale StandardScaler() 0 -> 0.5461152021613928
2606/3780 0.350 0.132 scale MinMaxScaler() 0 -> 0.5463208364965753
2607/3780 0.350 0.132 auto StandardScaler() 0 -> 0.5461152021613928
2608/3780 0.350 0.132 auto MinMaxScaler() 0 -> 0.5825701483991589
2609/3780 0.350 0.132 0.01 StandardScaler() 0 -> 0.5793404262130726
2610/3780 0.350 0.132 0.01 MinMaxScaler() 0 -> 0.7462009251759775
2611/3780 0.350 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5593663266310459
2612/3780 0.350 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6332993101146046
2613/3780 0.350 0.132 0.1 StandardScaler() 0 -> 0.546761857570606
2614/3780 0.350 0.132 0.1 MinMaxScaler() 0 -> 0.590363821923722
2615/3780 0.350 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5459421724391321
2616/3780 0.350 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5770656115753573
2617/3780 0.350 0.132 1.0 StandardScaler() 0 -> 0.5610872191107438
2618/3780 0.350 0.132 1.0 MinMaxScaler() 0 -> 0.5566194418785309
2619/3780 0.350 0.168 scale StandardScaler() 0 -> 0.5443262766923519
2620/3780 0.350 0.168 scale MinMaxScaler() 0 -> 0.5447058305771421
2621/3780 0.350 0.168 auto StandardScaler() 0 -> 0.5443262766923518
2622/3780 0.350 0.168 auto MinMaxScaler() 0 -> 0.5808142807807101
2623/3780 0.350 0.168 0.01 StandardScaler() 0 -> 0.5774900999531102
2624/3780 0.350 0.168 0.01 MinMaxScaler() 0 -> 0.7277836543137944
2625/3780 0.350 0.168 0.03162277660168379 StandardScaler() 0 -> 0.55702021245513
2626/3780 0.350 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6138318645137373
2627/3780 0.350 0.168 0.1 StandardScaler() 0 -> 0.5453590085916268
2628/3780 0.350 0.168 0.1 MinMaxScaler() 0 -> 0.5875986027506048
2629/3780 0.350 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5433397362458492
2630/3780 0.350 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5746717931609769
2631/3780 0.350 0.168 1.0 StandardScaler() 0 -> 0.5556004961209928
2632/3780 0.350 0.168 1.0 MinMaxScaler() 0 -> 0.55414581481242
2633/3780 0.350 0.213 scale StandardScaler() 0 -> 0.5424906190397677
2634/3780 0.350 0.213 scale MinMaxScaler() 0 -> 0.5426811571404432
2635/3780 0.350 0.213 auto StandardScaler() 0 -> 0.5424906190397676
2636/3780 0.350 0.213 auto MinMaxScaler() 0 -> 0.5792287670004911
2637/3780 0.350 0.213 0.01 StandardScaler() 0 -> 0.5753311383374093
2638/3780 0.350 0.213 0.01 MinMaxScaler() 0 -> 0.7060561340890259
2639/3780 0.350 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5542637306058505
2640/3780 0.350 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6039625250056054
2641/3780 0.350 0.213 0.1 StandardScaler() 0 -> 0.5436772972932006
2642/3780 0.350 0.213 0.1 MinMaxScaler() 0 -> 0.5857805549879206
2643/3780 0.350 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5416432159890233
2644/3780 0.350 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5720941496018295
2645/3780 0.350 0.213 1.0 StandardScaler() 0 -> 0.5499130803280664
2646/3780 0.350 0.213 1.0 MinMaxScaler() 0 -> 0.5519867757765534
2647/3780 0.350 0.270 scale StandardScaler() 0 -> 0.5404489483551423
2648/3780 0.350 0.270 scale MinMaxScaler() 0 -> 0.5407686282783511
2649/3780 0.350 0.270 auto StandardScaler() 0 -> 0.5404489483551422
2650/3780 0.350 0.270 auto MinMaxScaler() 0 -> 0.5775374640813036
2651/3780 0.350 0.270 0.01 StandardScaler() 0 -> 0.5730402109038021
2652/3780 0.350 0.270 0.01 MinMaxScaler() 0 -> 0.6813397143623426
2653/3780 0.350 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5520814112006006
2654/3780 0.350 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5983046588839568
2655/3780 0.350 0.270 0.1 StandardScaler() 0 -> 0.5424354098135055
2656/3780 0.350 0.270 0.1 MinMaxScaler() 0 -> 0.5843709701986965
2657/3780 0.350 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5399336317905656
2658/3780 0.350 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5695514585144913
2659/3780 0.350 0.270 1.0 StandardScaler() 0 -> 0.5457864492574448
2660/3780 0.350 0.270 1.0 MinMaxScaler() 0 -> 0.5494818510845533
2661/3780 0.350 0.342 scale StandardScaler() 0 -> 0.5389252446300328
2662/3780 0.350 0.342 scale MinMaxScaler() 0 -> 0.5393510308618272
2663/3780 0.350 0.342 auto StandardScaler() 0 -> 0.5389252446300326
2664/3780 0.350 0.342 auto MinMaxScaler() 0 -> 0.5754385321470509
2665/3780 0.350 0.342 0.01 StandardScaler() 0 -> 0.5707118771428648
2666/3780 0.350 0.342 0.01 MinMaxScaler() 0 -> 0.6544058476414034
2667/3780 0.350 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5503304265067726
2668/3780 0.350 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5938029296850403
2669/3780 0.350 0.342 0.1 StandardScaler() 0 -> 0.5410250448924755
2670/3780 0.350 0.342 0.1 MinMaxScaler() 0 -> 0.5831758747034677
2671/3780 0.350 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5384106456243923
2672/3780 0.350 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.567330428402994
2673/3780 0.350 0.342 1.0 StandardScaler() 0 -> 0.542933144416406
2674/3780 0.350 0.342 1.0 MinMaxScaler() 0 -> 0.547083074052625
2675/3780 0.350 0.434 scale StandardScaler() 0 -> 0.538225985713818
2676/3780 0.350 0.434 scale MinMaxScaler() 0 -> 0.5391087027519289
2677/3780 0.350 0.434 auto StandardScaler() 0 -> 0.5382259857138181
2678/3780 0.350 0.434 auto MinMaxScaler() 0 -> 0.5732517016910569
2679/3780 0.350 0.434 0.01 StandardScaler() 0 -> 0.5681759317076344
2680/3780 0.350 0.434 0.01 MinMaxScaler() 0 -> 0.6286942705281771
2681/3780 0.350 0.434 0.03162277660168379 StandardScaler() 0 -> 0.54802470142285
2682/3780 0.350 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5902274011997645
2683/3780 0.350 0.434 0.1 StandardScaler() 0 -> 0.539266746692914
2684/3780 0.350 0.434 0.1 MinMaxScaler() 0 -> 0.581855487741873
2685/3780 0.350 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5374105957289732
2686/3780 0.350 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5651359602434999
2687/3780 0.350 0.434 1.0 StandardScaler() 0 -> 0.5412114496339074
2688/3780 0.350 0.434 1.0 MinMaxScaler() 0 -> 0.545690511645989
2689/3780 0.350 0.551 scale StandardScaler() 0 -> 0.5375367684404793
2690/3780 0.350 0.551 scale MinMaxScaler() 0 -> 0.5379737770165508
2691/3780 0.350 0.551 auto StandardScaler() 0 -> 0.5375367684404788
2692/3780 0.350 0.551 auto MinMaxScaler() 0 -> 0.5709853345741501
2693/3780 0.350 0.551 0.01 StandardScaler() 0 -> 0.566037085286144
2694/3780 0.350 0.551 0.01 MinMaxScaler() 0 -> 0.6116481395510377
2695/3780 0.350 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5460490394137372
2696/3780 0.350 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5883241743290409
2697/3780 0.350 0.551 0.1 StandardScaler() 0 -> 0.538315089008937
2698/3780 0.350 0.551 0.1 MinMaxScaler() 0 -> 0.5807735676613567
2699/3780 0.350 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5369537774389846
2700/3780 0.350 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5628180427756383
2701/3780 0.350 0.551 1.0 StandardScaler() 0 -> 0.5407688565904437
2702/3780 0.350 0.551 1.0 MinMaxScaler() 0 -> 0.5447352082897771
2703/3780 0.350 0.700 scale StandardScaler() 0 -> 0.5368635001007216
2704/3780 0.350 0.700 scale MinMaxScaler() 0 -> 0.5369662866434807
2705/3780 0.350 0.700 auto StandardScaler() 0 -> 0.536863500100721
2706/3780 0.350 0.700 auto MinMaxScaler() 0 -> 0.5686940448262545
2707/3780 0.350 0.700 0.01 StandardScaler() 0 -> 0.5634160251721892
2708/3780 0.350 0.700 0.01 MinMaxScaler() 0 -> 0.6027487270642853
2709/3780 0.350 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5448893974479416
2710/3780 0.350 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5868754446977638
2711/3780 0.350 0.700 0.1 StandardScaler() 0 -> 0.5377622572875496
2712/3780 0.350 0.700 0.1 MinMaxScaler() 0 -> 0.5797441184103187
2713/3780 0.350 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5362832738097836
2714/3780 0.350 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5603209869793324
2715/3780 0.350 0.700 1.0 StandardScaler() 0 -> 0.5415634456522646
2716/3780 0.350 0.700 1.0 MinMaxScaler() 0 -> 0.5435567129723676
2717/3780 0.350 0.888 scale StandardScaler() 0 -> 0.5367293820997728
2718/3780 0.350 0.888 scale MinMaxScaler() 0 -> 0.5361572220657627
2719/3780 0.350 0.888 auto StandardScaler() 0 -> 0.5367293820997728
2720/3780 0.350 0.888 auto MinMaxScaler() 0 -> 0.5663861803968858
2721/3780 0.350 0.888 0.01 StandardScaler() 0 -> 0.5607345468705229
2722/3780 0.350 0.888 0.01 MinMaxScaler() 0 -> 0.5976306034872264
2723/3780 0.350 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5439856588013741
2724/3780 0.350 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.58599070356271
2725/3780 0.350 0.888 0.1 StandardScaler() 0 -> 0.5369966987375995
2726/3780 0.350 0.888 0.1 MinMaxScaler() 0 -> 0.5780792120530612
2727/3780 0.350 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5369518145993254
2728/3780 0.350 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5582087265245735
2729/3780 0.350 0.888 1.0 StandardScaler() 0 -> 0.5427804527243029
2730/3780 0.350 0.888 1.0 MinMaxScaler() 0 -> 0.5428783703207459
2731/3780 0.350 1.126 scale StandardScaler() 0 -> 0.5368814047916882
2732/3780 0.350 1.126 scale MinMaxScaler() 0 -> 0.5359005360592328
2733/3780 0.350 1.126 auto StandardScaler() 0 -> 0.5368814047916873
2734/3780 0.350 1.126 auto MinMaxScaler() 0 -> 0.5644474731008856
2735/3780 0.350 1.126 0.01 StandardScaler() 0 -> 0.5581408148791599
2736/3780 0.350 1.126 0.01 MinMaxScaler() 0 -> 0.5932298924572749
2737/3780 0.350 1.126 0.03162277660168379 StandardScaler() 0 -> 0.543279779106756
2738/3780 0.350 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5851124603028799
2739/3780 0.350 1.126 0.1 StandardScaler() 0 -> 0.5371394319079315
2740/3780 0.350 1.126 0.1 MinMaxScaler() 0 -> 0.5762670573073456
2741/3780 0.350 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5374269251950916
2742/3780 0.350 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5557729501227535
2743/3780 0.350 1.126 1.0 StandardScaler() 0 -> 0.5450591337124556
2744/3780 0.350 1.126 1.0 MinMaxScaler() 0 -> 0.5419175777257031
2745/3780 0.350 1.429 scale StandardScaler() 0 -> 0.5373583027545055
2746/3780 0.350 1.429 scale MinMaxScaler() 0 -> 0.5367540121808516
2747/3780 0.350 1.429 auto StandardScaler() 0 -> 0.5373583027545047
2748/3780 0.350 1.429 auto MinMaxScaler() 0 -> 0.562159838269772
2749/3780 0.350 1.429 0.01 StandardScaler() 0 -> 0.5560919982833447
2750/3780 0.350 1.429 0.01 MinMaxScaler() 0 -> 0.5900967186050394
2751/3780 0.350 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5423792359506439
2752/3780 0.350 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5845048306576451
2753/3780 0.350 1.429 0.1 StandardScaler() 0 -> 0.5364368221260888
2754/3780 0.350 1.429 0.1 MinMaxScaler() 0 -> 0.5744918488999361
2755/3780 0.350 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5398577862549055
2756/3780 0.350 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5538172201794808
2757/3780 0.350 1.429 1.0 StandardScaler() 0 -> 0.5486903052558568
2758/3780 0.350 1.429 1.0 MinMaxScaler() 0 -> 0.5411613921874064
2759/3780 0.350 1.814 scale StandardScaler() 0 -> 0.5386661928898091
2760/3780 0.350 1.814 scale MinMaxScaler() 0 -> 0.5370646431008581
2761/3780 0.350 1.814 auto StandardScaler() 0 -> 0.538666192889809
2762/3780 0.350 1.814 auto MinMaxScaler() 0 -> 0.5596628050683273
2763/3780 0.350 1.814 0.01 StandardScaler() 0 -> 0.5537450804424956
2764/3780 0.350 1.814 0.01 MinMaxScaler() 0 -> 0.5884674412933942
2765/3780 0.350 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5418326629118178
2766/3780 0.350 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.583901078939542
2767/3780 0.350 1.814 0.1 StandardScaler() 0 -> 0.5364898261019198
2768/3780 0.350 1.814 0.1 MinMaxScaler() 0 -> 0.5725967906476906
2769/3780 0.350 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5424074732722414
2770/3780 0.350 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5515570835661006
2771/3780 0.350 1.814 1.0 StandardScaler() 0 -> 0.5522376618394214
2772/3780 0.350 1.814 1.0 MinMaxScaler() 0 -> 0.5406330741771911
2773/3780 0.350 2.302 scale StandardScaler() 0 -> 0.5398276542371998
2774/3780 0.350 2.302 scale MinMaxScaler() 0 -> 0.5375329735592933
2775/3780 0.350 2.302 auto StandardScaler() 0 -> 0.5398276542371998
2776/3780 0.350 2.302 auto MinMaxScaler() 0 -> 0.5574709369584773
2777/3780 0.350 2.302 0.01 StandardScaler() 0 -> 0.551901144943529
2778/3780 0.350 2.302 0.01 MinMaxScaler() 0 -> 0.5873765421660105
2779/3780 0.350 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5411270886413532
2780/3780 0.350 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5834873779428941
2781/3780 0.350 2.302 0.1 StandardScaler() 0 -> 0.5369479013192634
2782/3780 0.350 2.302 0.1 MinMaxScaler() 0 -> 0.5701176364890447
2783/3780 0.350 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5450655984127036
2784/3780 0.350 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5499998362285963
2785/3780 0.350 2.302 1.0 StandardScaler() 0 -> 0.5565392083256916
2786/3780 0.350 2.302 1.0 MinMaxScaler() 0 -> 0.5393553380102597
2787/3780 0.350 2.921 scale StandardScaler() 0 -> 0.5417317814957161
2788/3780 0.350 2.921 scale MinMaxScaler() 0 -> 0.539041617410698
2789/3780 0.350 2.921 auto StandardScaler() 0 -> 0.5417317814957144
2790/3780 0.350 2.921 auto MinMaxScaler() 0 -> 0.5552118319511834
2791/3780 0.350 2.921 0.01 StandardScaler() 0 -> 0.5506604245844159
2792/3780 0.350 2.921 0.01 MinMaxScaler() 0 -> 0.5863873030722169
2793/3780 0.350 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5402944809407624
2794/3780 0.350 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5828391534071266
2795/3780 0.350 2.921 0.1 StandardScaler() 0 -> 0.5380688932502591
2796/3780 0.350 2.921 0.1 MinMaxScaler() 0 -> 0.5678403329012359
2797/3780 0.350 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5491896107824578
2798/3780 0.350 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5484576730011286
2799/3780 0.350 2.921 1.0 StandardScaler() 0 -> 0.562387501305487
2800/3780 0.350 2.921 1.0 MinMaxScaler() 0 -> 0.538587651208733
2801/3780 0.350 3.707 scale StandardScaler() 0 -> 0.5436232692037944
2802/3780 0.350 3.707 scale MinMaxScaler() 0 -> 0.5412411628359028
2803/3780 0.350 3.707 auto StandardScaler() 0 -> 0.5436232692037958
2804/3780 0.350 3.707 auto MinMaxScaler() 0 -> 0.5532129321598847
2805/3780 0.350 3.707 0.01 StandardScaler() 0 -> 0.5488082595407265
2806/3780 0.350 3.707 0.01 MinMaxScaler() 0 -> 0.5858464051706158
2807/3780 0.350 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5395972910076051
2808/3780 0.350 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5821363226872031
2809/3780 0.350 3.707 0.1 StandardScaler() 0 -> 0.5393684406960855
2810/3780 0.350 3.707 0.1 MinMaxScaler() 0 -> 0.5655487445332436
2811/3780 0.350 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5531014695001925
2812/3780 0.350 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5478183609970446
2813/3780 0.350 3.707 1.0 StandardScaler() 0 -> 0.5709155808705503
2814/3780 0.350 3.707 1.0 MinMaxScaler() 0 -> 0.5377258294492177
2815/3780 0.350 4.703 scale StandardScaler() 0 -> 0.5452091620139975
2816/3780 0.350 4.703 scale MinMaxScaler() 0 -> 0.5431322463535726
2817/3780 0.350 4.703 auto StandardScaler() 0 -> 0.5452091620139977
2818/3780 0.350 4.703 auto MinMaxScaler() 0 -> 0.5514862672111279
2819/3780 0.350 4.703 0.01 StandardScaler() 0 -> 0.5480527891010402
2820/3780 0.350 4.703 0.01 MinMaxScaler() 0 -> 0.5853665373129519
2821/3780 0.350 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5386955061056597
2822/3780 0.350 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5811319166836362
2823/3780 0.350 4.703 0.1 StandardScaler() 0 -> 0.5401469312736028
2824/3780 0.350 4.703 0.1 MinMaxScaler() 0 -> 0.5638522047307613
2825/3780 0.350 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5570456174482797
2826/3780 0.350 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5467837001122776
2827/3780 0.350 4.703 1.0 StandardScaler() 0 -> 0.5823767586321276
2828/3780 0.350 4.703 1.0 MinMaxScaler() 0 -> 0.5371833138412035
2829/3780 0.350 5.968 scale StandardScaler() 0 -> 0.5490113167848883
2830/3780 0.350 5.968 scale MinMaxScaler() 0 -> 0.5454489646925028
2831/3780 0.350 5.968 auto StandardScaler() 0 -> 0.5490113167848892
2832/3780 0.350 5.968 auto MinMaxScaler() 0 -> 0.5503419018855388
2833/3780 0.350 5.968 0.01 StandardScaler() 0 -> 0.5473357562955504
2834/3780 0.350 5.968 0.01 MinMaxScaler() 0 -> 0.585202834650126
2835/3780 0.350 5.968 0.03162277660168379 StandardScaler() 0 -> 0.5377985886746942
2836/3780 0.350 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5799196069328744
2837/3780 0.350 5.968 0.1 StandardScaler() 0 -> 0.5407110681975532
2838/3780 0.350 5.968 0.1 MinMaxScaler() 0 -> 0.5615251857536109
2839/3780 0.350 5.968 0.31622776601683794 StandardScaler() 0 -> 0.562246374887296
2840/3780 0.350 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5459080497523688
2841/3780 0.350 5.968 1.0 StandardScaler() 0 -> 0.5954169564158595
2842/3780 0.350 5.968 1.0 MinMaxScaler() 0 -> 0.5370533262031615
2843/3780 0.350 7.574 scale StandardScaler() 0 -> 0.5535134408010939
2844/3780 0.350 7.574 scale MinMaxScaler() 0 -> 0.5497933175347407
2845/3780 0.350 7.574 auto StandardScaler() 0 -> 0.5535134408010931
2846/3780 0.350 7.574 auto MinMaxScaler() 0 -> 0.5488844837545341
2847/3780 0.350 7.574 0.01 StandardScaler() 0 -> 0.5466871503929159
2848/3780 0.350 7.574 0.01 MinMaxScaler() 0 -> 0.5850441900785112
2849/3780 0.350 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5374544262030437
2850/3780 0.350 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5786809706048227
2851/3780 0.350 7.574 0.1 StandardScaler() 0 -> 0.5421149674934755
2852/3780 0.350 7.574 0.1 MinMaxScaler() 0 -> 0.5587955366719843
2853/3780 0.350 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5668096107090731
2854/3780 0.350 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5452625001863717
2855/3780 0.350 7.574 1.0 StandardScaler() 0 -> 0.6092399505082243
2856/3780 0.350 7.574 1.0 MinMaxScaler() 0 -> 0.5368144370649744
2857/3780 0.350 9.611 scale StandardScaler() 0 -> 0.5586140899585889
2858/3780 0.350 9.611 scale MinMaxScaler() 0 -> 0.5543526433570679
2859/3780 0.350 9.611 auto StandardScaler() 0 -> 0.5586140899585824
2860/3780 0.350 9.611 auto MinMaxScaler() 0 -> 0.548098079799818
2861/3780 0.350 9.611 0.01 StandardScaler() 0 -> 0.5462691477468374
2862/3780 0.350 9.611 0.01 MinMaxScaler() 0 -> 0.5848440641742586
2863/3780 0.350 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5371616336738362
2864/3780 0.350 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.576937453951865
2865/3780 0.350 9.611 0.1 StandardScaler() 0 -> 0.5438787474681456
2866/3780 0.350 9.611 0.1 MinMaxScaler() 0 -> 0.5567776969729761
2867/3780 0.350 9.611 0.31622776601683794 StandardScaler() 0 -> 0.573186236748076
2868/3780 0.350 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5445717994711663
2869/3780 0.350 9.611 1.0 StandardScaler() 0 -> 0.6221823057504278
2870/3780 0.350 9.611 1.0 MinMaxScaler() 0 -> 0.5367430181717573
2871/3780 0.350 12.196 scale StandardScaler() 0 -> 0.5642751133773938
2872/3780 0.350 12.196 scale MinMaxScaler() 0 -> 0.5582392623000909
2873/3780 0.350 12.196 auto StandardScaler() 0 -> 0.564275113377397
2874/3780 0.350 12.196 auto MinMaxScaler() 0 -> 0.5472864582633938
2875/3780 0.350 12.196 0.01 StandardScaler() 0 -> 0.54526334822105
2876/3780 0.350 12.196 0.01 MinMaxScaler() 0 -> 0.5846326716953506
2877/3780 0.350 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5369052087270755
2878/3780 0.350 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5752590019985373
2879/3780 0.350 12.196 0.1 StandardScaler() 0 -> 0.5458062721140791
2880/3780 0.350 12.196 0.1 MinMaxScaler() 0 -> 0.5547397973289204
2881/3780 0.350 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5805356807565419
2882/3780 0.350 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5439161390708998
2883/3780 0.350 12.196 1.0 StandardScaler() 0 -> 0.6362117044798118
2884/3780 0.350 12.196 1.0 MinMaxScaler() 0 -> 0.5366776792257376
2885/3780 0.350 15.476 scale StandardScaler() 0 -> 0.5695136949133399
2886/3780 0.350 15.476 scale MinMaxScaler() 0 -> 0.562182932530849
2887/3780 0.350 15.476 auto StandardScaler() 0 -> 0.5695136949133436
2888/3780 0.350 15.476 auto MinMaxScaler() 0 -> 0.5462825598097294
2889/3780 0.350 15.476 0.01 StandardScaler() 0 -> 0.5445845878468795
2890/3780 0.350 15.476 0.01 MinMaxScaler() 0 -> 0.5843422647511981
2891/3780 0.350 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5368367044942113
2892/3780 0.350 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5733402960756148
2893/3780 0.350 15.476 0.1 StandardScaler() 0 -> 0.5462299401508964
2894/3780 0.350 15.476 0.1 MinMaxScaler() 0 -> 0.5532157092230442
2895/3780 0.350 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5876663121933318
2896/3780 0.350 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5432367284570154
2897/3780 0.350 15.476 1.0 StandardScaler() 0 -> 0.6513748146332956
2898/3780 0.350 15.476 1.0 MinMaxScaler() 0 -> 0.5370409361005403
2899/3780 0.350 19.638 scale StandardScaler() 0 -> 0.5756900993288667
2900/3780 0.350 19.638 scale MinMaxScaler() 0 -> 0.5673114750345606
2901/3780 0.350 19.638 auto StandardScaler() 0 -> 0.5756900993288534
2902/3780 0.350 19.638 auto MinMaxScaler() 0 -> 0.5459777673230876
2903/3780 0.350 19.638 0.01 StandardScaler() 0 -> 0.5443292471167761
2904/3780 0.350 19.638 0.01 MinMaxScaler() 0 -> 0.5837934917876583
2905/3780 0.350 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5366357304711924
2906/3780 0.350 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5715090182970025
2907/3780 0.350 19.638 0.1 StandardScaler() 0 -> 0.5464485953308471
2908/3780 0.350 19.638 0.1 MinMaxScaler() 0 -> 0.5517775346402879
2909/3780 0.350 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5979426032166265
2910/3780 0.350 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5429643468141991
2911/3780 0.350 19.638 1.0 StandardScaler() 0 -> 0.6682398590330568
2912/3780 0.350 19.638 1.0 MinMaxScaler() 0 -> 0.5369419226973359
2913/3780 0.350 24.920 scale StandardScaler() 0 -> 0.5816995748353864
2914/3780 0.350 24.920 scale MinMaxScaler() 0 -> 0.5722077409486728
2915/3780 0.350 24.920 auto StandardScaler() 0 -> 0.5816995748353849
2916/3780 0.350 24.920 auto MinMaxScaler() 0 -> 0.5455280363015249
2917/3780 0.350 24.920 0.01 StandardScaler() 0 -> 0.5439271806730215
2918/3780 0.350 24.920 0.01 MinMaxScaler() 0 -> 0.5833324581597084
2919/3780 0.350 24.920 0.03162277660168379 StandardScaler() 0 -> 0.537064790246296
2920/3780 0.350 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5689343620335056
2921/3780 0.350 24.920 0.1 StandardScaler() 0 -> 0.5483105038513896
2922/3780 0.350 24.920 0.1 MinMaxScaler() 0 -> 0.550345932331465
2923/3780 0.350 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6096497767445298
2924/3780 0.350 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5425585255909349
2925/3780 0.350 24.920 1.0 StandardScaler() 0 -> 0.6871727523002562
2926/3780 0.350 24.920 1.0 MinMaxScaler() 0 -> 0.5371876790907657
2927/3780 0.350 31.623 scale StandardScaler() 0 -> 0.587211856282826
2928/3780 0.350 31.623 scale MinMaxScaler() 0 -> 0.5776392904402781
2929/3780 0.350 31.623 auto StandardScaler() 0 -> 0.5872118562828245
2930/3780 0.350 31.623 auto MinMaxScaler() 0 -> 0.5448662916546744
2931/3780 0.350 31.623 0.01 StandardScaler() 0 -> 0.5434913281656638
2932/3780 0.350 31.623 0.01 MinMaxScaler() 0 -> 0.582621135464705
2933/3780 0.350 31.623 0.03162277660168379 StandardScaler() 0 -> 0.53746855107908
2934/3780 0.350 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5667695211655465
2935/3780 0.350 31.623 0.1 StandardScaler() 0 -> 0.5510345944212155
2936/3780 0.350 31.623 0.1 MinMaxScaler() 0 -> 0.5491682918637331
2937/3780 0.350 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6212606932989656
2938/3780 0.350 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5420213779149224
2939/3780 0.350 31.623 1.0 StandardScaler() 0 -> 0.7119606967389162
2940/3780 0.350 31.623 1.0 MinMaxScaler() 0 -> 0.5376770687770841
2941/3780 0.400 0.032 scale StandardScaler() 0 -> 0.5666379343874678
2942/3780 0.400 0.032 scale MinMaxScaler() 0 -> 0.5641471994840132
2943/3780 0.400 0.032 auto StandardScaler() 0 -> 0.5666379343874678
2944/3780 0.400 0.032 auto MinMaxScaler() 0 -> 0.6088522713885284
2945/3780 0.400 0.032 0.01 StandardScaler() 0 -> 0.6056095880098441
2946/3780 0.400 0.032 0.01 MinMaxScaler() 0 -> 0.8321739487216999
2947/3780 0.400 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5797422430829902
2948/3780 0.400 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7888547393512289
2949/3780 0.400 0.032 0.1 StandardScaler() 0 -> 0.5652357363286896
2950/3780 0.400 0.032 0.1 MinMaxScaler() 0 -> 0.6830517030362966
2951/3780 0.400 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5722504284061221
2952/3780 0.400 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5941996692959958
2953/3780 0.400 0.032 1.0 StandardScaler() 0 -> 0.6379605463886745
2954/3780 0.400 0.032 1.0 MinMaxScaler() 0 -> 0.5755499112777266
2955/3780 0.400 0.040 scale StandardScaler() 0 -> 0.5632061345035183
2956/3780 0.400 0.040 scale MinMaxScaler() 0 -> 0.5614247011413769
2957/3780 0.400 0.040 auto StandardScaler() 0 -> 0.5632061345035182
2958/3780 0.400 0.040 auto MinMaxScaler() 0 -> 0.5986063745643061
2959/3780 0.400 0.040 0.01 StandardScaler() 0 -> 0.5962788934837914
2960/3780 0.400 0.040 0.01 MinMaxScaler() 0 -> 0.826475087794579
2961/3780 0.400 0.040 0.03162277660168379 StandardScaler() 0 -> 0.576109276388221
2962/3780 0.400 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7729356104398285
2963/3780 0.400 0.040 0.1 StandardScaler() 0 -> 0.5619716064163617
2964/3780 0.400 0.040 0.1 MinMaxScaler() 0 -> 0.6526033967568651
2965/3780 0.400 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5673695595486444
2966/3780 0.400 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5903889309402524
2967/3780 0.400 0.040 1.0 StandardScaler() 0 -> 0.617669351561616
2968/3780 0.400 0.040 1.0 MinMaxScaler() 0 -> 0.5727063833468026
2969/3780 0.400 0.051 scale StandardScaler() 0 -> 0.5598771822823121
2970/3780 0.400 0.051 scale MinMaxScaler() 0 -> 0.5592503232301943
2971/3780 0.400 0.051 auto StandardScaler() 0 -> 0.5598771822823121
2972/3780 0.400 0.051 auto MinMaxScaler() 0 -> 0.5940268546194676
2973/3780 0.400 0.051 0.01 StandardScaler() 0 -> 0.591614264911405
2974/3780 0.400 0.051 0.01 MinMaxScaler() 0 -> 0.8193098481555084
2975/3780 0.400 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5726255783376409
2976/3780 0.400 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7535998117547331
2977/3780 0.400 0.051 0.1 StandardScaler() 0 -> 0.5593677274816563
2978/3780 0.400 0.051 0.1 MinMaxScaler() 0 -> 0.624368194153149
2979/3780 0.400 0.051 0.31622776601683794 StandardScaler() 0 -> 0.56295242653336
2980/3780 0.400 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5861232748689164
2981/3780 0.400 0.051 1.0 StandardScaler() 0 -> 0.6021287757301789
2982/3780 0.400 0.051 1.0 MinMaxScaler() 0 -> 0.5699583193362029
2983/3780 0.400 0.065 scale StandardScaler() 0 -> 0.5568761287252623
2984/3780 0.400 0.065 scale MinMaxScaler() 0 -> 0.5569817580418758
2985/3780 0.400 0.065 auto StandardScaler() 0 -> 0.5568761287252623
2986/3780 0.400 0.065 auto MinMaxScaler() 0 -> 0.5908144137388908
2987/3780 0.400 0.065 0.01 StandardScaler() 0 -> 0.5874919380748849
2988/3780 0.400 0.065 0.01 MinMaxScaler() 0 -> 0.8104604732735082
2989/3780 0.400 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5700935841192059
2990/3780 0.400 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.7307346275569583
2991/3780 0.400 0.065 0.1 StandardScaler() 0 -> 0.5569647677830201
2992/3780 0.400 0.065 0.1 MinMaxScaler() 0 -> 0.6058994212005295
2993/3780 0.400 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5589382699826236
2994/3780 0.400 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5835897090500939
2995/3780 0.400 0.065 1.0 StandardScaler() 0 -> 0.5894964244916183
2996/3780 0.400 0.065 1.0 MinMaxScaler() 0 -> 0.5673411723622123
2997/3780 0.400 0.082 scale StandardScaler() 0 -> 0.5541178646998
2998/3780 0.400 0.082 scale MinMaxScaler() 0 -> 0.5547113389181658
2999/3780 0.400 0.082 auto StandardScaler() 0 -> 0.5541178646998
3000/3780 0.400 0.082 auto MinMaxScaler() 0 -> 0.5867773178709491
3001/3780 0.400 0.082 0.01 StandardScaler() 0 -> 0.5839525157402968
3002/3780 0.400 0.082 0.01 MinMaxScaler() 0 -> 0.7994485404489043
3003/3780 0.400 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5671604029315641
3004/3780 0.400 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.7042788475305111
3005/3780 0.400 0.082 0.1 StandardScaler() 0 -> 0.5546002795927665
3006/3780 0.400 0.082 0.1 MinMaxScaler() 0 -> 0.5980687941947755
3007/3780 0.400 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5552892132256467
3008/3780 0.400 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5816985217961069
3009/3780 0.400 0.082 1.0 StandardScaler() 0 -> 0.5797546511292601
3010/3780 0.400 0.082 1.0 MinMaxScaler() 0 -> 0.5645466014795959
3011/3780 0.400 0.104 scale StandardScaler() 0 -> 0.5518864986840022
3012/3780 0.400 0.104 scale MinMaxScaler() 0 -> 0.5527184766098107
3013/3780 0.400 0.104 auto StandardScaler() 0 -> 0.5518864986840022
3014/3780 0.400 0.104 auto MinMaxScaler() 0 -> 0.584691424326809
3015/3780 0.400 0.104 0.01 StandardScaler() 0 -> 0.5819786675636319
3016/3780 0.400 0.104 0.01 MinMaxScaler() 0 -> 0.785877807213495
3017/3780 0.400 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5645397785546727
3018/3780 0.400 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6748987012694219
3019/3780 0.400 0.104 0.1 StandardScaler() 0 -> 0.5530652256561064
3020/3780 0.400 0.104 0.1 MinMaxScaler() 0 -> 0.5937357101975255
3021/3780 0.400 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5519566286929375
3022/3780 0.400 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5795357776214259
3023/3780 0.400 0.104 1.0 StandardScaler() 0 -> 0.5710703273665102
3024/3780 0.400 0.104 1.0 MinMaxScaler() 0 -> 0.5622191520163539
3025/3780 0.400 0.132 scale StandardScaler() 0 -> 0.5495307866704792
3026/3780 0.400 0.132 scale MinMaxScaler() 0 -> 0.5513139278617966
3027/3780 0.400 0.132 auto StandardScaler() 0 -> 0.5495307866704789
3028/3780 0.400 0.132 auto MinMaxScaler() 0 -> 0.5830852103366562
3029/3780 0.400 0.132 0.01 StandardScaler() 0 -> 0.5797091529169355
3030/3780 0.400 0.132 0.01 MinMaxScaler() 0 -> 0.7693204446962518
3031/3780 0.400 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5619300926268131
3032/3780 0.400 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6449640545484064
3033/3780 0.400 0.132 0.1 StandardScaler() 0 -> 0.5511001091691914
3034/3780 0.400 0.132 0.1 MinMaxScaler() 0 -> 0.5907451043913715
3035/3780 0.400 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5483908537343777
3036/3780 0.400 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5773513286087834
3037/3780 0.400 0.132 1.0 StandardScaler() 0 -> 0.564260303575796
3038/3780 0.400 0.132 1.0 MinMaxScaler() 0 -> 0.5602633249710034
3039/3780 0.400 0.168 scale StandardScaler() 0 -> 0.5477156283920402
3040/3780 0.400 0.168 scale MinMaxScaler() 0 -> 0.5497740505970256
3041/3780 0.400 0.168 auto StandardScaler() 0 -> 0.5477156283920402
3042/3780 0.400 0.168 auto MinMaxScaler() 0 -> 0.5813614994638093
3043/3780 0.400 0.168 0.01 StandardScaler() 0 -> 0.5779420970914527
3044/3780 0.400 0.168 0.01 MinMaxScaler() 0 -> 0.7492708733275473
3045/3780 0.400 0.168 0.03162277660168379 StandardScaler() 0 -> 0.559514574764306
3046/3780 0.400 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6179860383369818
3047/3780 0.400 0.168 0.1 StandardScaler() 0 -> 0.5492179978220801
3048/3780 0.400 0.168 0.1 MinMaxScaler() 0 -> 0.5876478451049671
3049/3780 0.400 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5459302544598358
3050/3780 0.400 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5751281723477928
3051/3780 0.400 0.168 1.0 StandardScaler() 0 -> 0.5581458270621926
3052/3780 0.400 0.168 1.0 MinMaxScaler() 0 -> 0.5582164242804531
3053/3780 0.400 0.213 scale StandardScaler() 0 -> 0.5460500510420442
3054/3780 0.400 0.213 scale MinMaxScaler() 0 -> 0.5477958391577401
3055/3780 0.400 0.213 auto StandardScaler() 0 -> 0.5460500510420441
3056/3780 0.400 0.213 auto MinMaxScaler() 0 -> 0.579490873107531
3057/3780 0.400 0.213 0.01 StandardScaler() 0 -> 0.5760349028169184
3058/3780 0.400 0.213 0.01 MinMaxScaler() 0 -> 0.7256632034371892
3059/3780 0.400 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5568973150996713
3060/3780 0.400 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6039655942355928
3061/3780 0.400 0.213 0.1 StandardScaler() 0 -> 0.5485684842370545
3062/3780 0.400 0.213 0.1 MinMaxScaler() 0 -> 0.5860779630222361
3063/3780 0.400 0.213 0.31622776601683794 StandardScaler() 0 -> 0.54409857750945
3064/3780 0.400 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5731610310771533
3065/3780 0.400 0.213 1.0 StandardScaler() 0 -> 0.5525404616264796
3066/3780 0.400 0.213 1.0 MinMaxScaler() 0 -> 0.5559380070003734
3067/3780 0.400 0.270 scale StandardScaler() 0 -> 0.5447200812243217
3068/3780 0.400 0.270 scale MinMaxScaler() 0 -> 0.5458383100645897
3069/3780 0.400 0.270 auto StandardScaler() 0 -> 0.5447200812243215
3070/3780 0.400 0.270 auto MinMaxScaler() 0 -> 0.5778330966962556
3071/3780 0.400 0.270 0.01 StandardScaler() 0 -> 0.5738994717267011
3072/3780 0.400 0.270 0.01 MinMaxScaler() 0 -> 0.698474273999606
3073/3780 0.400 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5547435925043405
3074/3780 0.400 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5973468388322759
3075/3780 0.400 0.270 0.1 StandardScaler() 0 -> 0.5474305476174379
3076/3780 0.400 0.270 0.1 MinMaxScaler() 0 -> 0.5846067553868802
3077/3780 0.400 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5426950118248464
3078/3780 0.400 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5711038487991439
3079/3780 0.400 0.270 1.0 StandardScaler() 0 -> 0.5487290995942495
3080/3780 0.400 0.270 1.0 MinMaxScaler() 0 -> 0.5541646891256294
3081/3780 0.400 0.342 scale StandardScaler() 0 -> 0.5434773495318641
3082/3780 0.400 0.342 scale MinMaxScaler() 0 -> 0.5445406043091746
3083/3780 0.400 0.342 auto StandardScaler() 0 -> 0.543477349531864
3084/3780 0.400 0.342 auto MinMaxScaler() 0 -> 0.5759254218602515
3085/3780 0.400 0.342 0.01 StandardScaler() 0 -> 0.5718661532641524
3086/3780 0.400 0.342 0.01 MinMaxScaler() 0 -> 0.6688193956972032
3087/3780 0.400 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5529955413634303
3088/3780 0.400 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5938948195241026
3089/3780 0.400 0.342 0.1 StandardScaler() 0 -> 0.5455681188103018
3090/3780 0.400 0.342 0.1 MinMaxScaler() 0 -> 0.5835062400423395
3091/3780 0.400 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5418014525409306
3092/3780 0.400 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5691899232428251
3093/3780 0.400 0.342 1.0 StandardScaler() 0 -> 0.5462269933376593
3094/3780 0.400 0.342 1.0 MinMaxScaler() 0 -> 0.5525000704802147
3095/3780 0.400 0.434 scale StandardScaler() 0 -> 0.542107964503958
3096/3780 0.400 0.434 scale MinMaxScaler() 0 -> 0.5430876173091921
3097/3780 0.400 0.434 auto StandardScaler() 0 -> 0.5421079645039582
3098/3780 0.400 0.434 auto MinMaxScaler() 0 -> 0.5741721786138657
3099/3780 0.400 0.434 0.01 StandardScaler() 0 -> 0.5696072967505871
3100/3780 0.400 0.434 0.01 MinMaxScaler() 0 -> 0.6397876974878217
3101/3780 0.400 0.434 0.03162277660168379 StandardScaler() 0 -> 0.55120441246035
3102/3780 0.400 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.590591349232098
3103/3780 0.400 0.434 0.1 StandardScaler() 0 -> 0.5435576152339897
3104/3780 0.400 0.434 0.1 MinMaxScaler() 0 -> 0.5823621866218808
3105/3780 0.400 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5404652032198901
3106/3780 0.400 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5669517020988887
3107/3780 0.400 0.434 1.0 StandardScaler() 0 -> 0.5445786530986901
3108/3780 0.400 0.434 1.0 MinMaxScaler() 0 -> 0.5507868339316379
3109/3780 0.400 0.551 scale StandardScaler() 0 -> 0.540752415516117
3110/3780 0.400 0.551 scale MinMaxScaler() 0 -> 0.5419978252192856
3111/3780 0.400 0.551 auto StandardScaler() 0 -> 0.5407524155161167
3112/3780 0.400 0.551 auto MinMaxScaler() 0 -> 0.5721245938860812
3113/3780 0.400 0.551 0.01 StandardScaler() 0 -> 0.5672053842368553
3114/3780 0.400 0.551 0.01 MinMaxScaler() 0 -> 0.6141901402539963
3115/3780 0.400 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5498577512927584
3116/3780 0.400 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5883107243706411
3117/3780 0.400 0.551 0.1 StandardScaler() 0 -> 0.5420662840650303
3118/3780 0.400 0.551 0.1 MinMaxScaler() 0 -> 0.5810998022869212
3119/3780 0.400 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5387891885897208
3120/3780 0.400 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5646846994131405
3121/3780 0.400 0.551 1.0 StandardScaler() 0 -> 0.5429781379327999
3122/3780 0.400 0.551 1.0 MinMaxScaler() 0 -> 0.5499724177698255
3123/3780 0.400 0.700 scale StandardScaler() 0 -> 0.5392622590549778
3124/3780 0.400 0.700 scale MinMaxScaler() 0 -> 0.5405795463601002
3125/3780 0.400 0.700 auto StandardScaler() 0 -> 0.5392622590549774
3126/3780 0.400 0.700 auto MinMaxScaler() 0 -> 0.570316578217046
3127/3780 0.400 0.700 0.01 StandardScaler() 0 -> 0.5650646402492062
3128/3780 0.400 0.700 0.01 MinMaxScaler() 0 -> 0.6025385136922746
3129/3780 0.400 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5492699185534633
3130/3780 0.400 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.587051472198885
3131/3780 0.400 0.700 0.1 StandardScaler() 0 -> 0.5406903475045287
3132/3780 0.400 0.700 0.1 MinMaxScaler() 0 -> 0.5796699200262485
3133/3780 0.400 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5378512405074768
3134/3780 0.400 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5628389208793643
3135/3780 0.400 0.700 1.0 StandardScaler() 0 -> 0.5427920453606995
3136/3780 0.400 0.700 1.0 MinMaxScaler() 0 -> 0.5491045986066051
3137/3780 0.400 0.888 scale StandardScaler() 0 -> 0.5386535356440806
3138/3780 0.400 0.888 scale MinMaxScaler() 0 -> 0.5399030310103062
3139/3780 0.400 0.888 auto StandardScaler() 0 -> 0.5386535356440803
3140/3780 0.400 0.888 auto MinMaxScaler() 0 -> 0.5679625949183612
3141/3780 0.400 0.888 0.01 StandardScaler() 0 -> 0.5624287576862087
3142/3780 0.400 0.888 0.01 MinMaxScaler() 0 -> 0.596531167946042
3143/3780 0.400 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5484500365304977
3144/3780 0.400 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5861481417932074
3145/3780 0.400 0.888 0.1 StandardScaler() 0 -> 0.5405333736329351
3146/3780 0.400 0.888 0.1 MinMaxScaler() 0 -> 0.5782964569236045
3147/3780 0.400 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5379908727575451
3148/3780 0.400 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5608616708026876
3149/3780 0.400 0.888 1.0 StandardScaler() 0 -> 0.5429125289260294
3150/3780 0.400 0.888 1.0 MinMaxScaler() 0 -> 0.5481723828056017
3151/3780 0.400 1.126 scale StandardScaler() 0 -> 0.5388332453878785
3152/3780 0.400 1.126 scale MinMaxScaler() 0 -> 0.5400085816194142
3153/3780 0.400 1.126 auto StandardScaler() 0 -> 0.538833245387878
3154/3780 0.400 1.126 auto MinMaxScaler() 0 -> 0.5659878867177079
3155/3780 0.400 1.126 0.01 StandardScaler() 0 -> 0.5602808837412528
3156/3780 0.400 1.126 0.01 MinMaxScaler() 0 -> 0.5932185888151006
3157/3780 0.400 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5474724249775771
3158/3780 0.400 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5854911405791354
3159/3780 0.400 1.126 0.1 StandardScaler() 0 -> 0.5405564851730145
3160/3780 0.400 1.126 0.1 MinMaxScaler() 0 -> 0.5765467165871216
3161/3780 0.400 1.126 0.31622776601683794 StandardScaler() 0 -> 0.5395023273910394
3162/3780 0.400 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.558975523526465
3163/3780 0.400 1.126 1.0 StandardScaler() 0 -> 0.5435073983441666
3164/3780 0.400 1.126 1.0 MinMaxScaler() 0 -> 0.5469129043188571
3165/3780 0.400 1.429 scale StandardScaler() 0 -> 0.5388522575781413
3166/3780 0.400 1.429 scale MinMaxScaler() 0 -> 0.5397511113567601
3167/3780 0.400 1.429 auto StandardScaler() 0 -> 0.5388522575781405
3168/3780 0.400 1.429 auto MinMaxScaler() 0 -> 0.5638930535412197
3169/3780 0.400 1.429 0.01 StandardScaler() 0 -> 0.5586266883187683
3170/3780 0.400 1.429 0.01 MinMaxScaler() 0 -> 0.5903477312328903
3171/3780 0.400 1.429 0.03162277660168379 StandardScaler() 0 -> 0.546714111006402
3172/3780 0.400 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5848355081828206
3173/3780 0.400 1.429 0.1 StandardScaler() 0 -> 0.5403435898218368
3174/3780 0.400 1.429 0.1 MinMaxScaler() 0 -> 0.5751241326281971
3175/3780 0.400 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5413962739774502
3176/3780 0.400 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5573431565156596
3177/3780 0.400 1.429 1.0 StandardScaler() 0 -> 0.5456494440173918
3178/3780 0.400 1.429 1.0 MinMaxScaler() 0 -> 0.5459111999160551
3179/3780 0.400 1.814 scale StandardScaler() 0 -> 0.539210105793248
3180/3780 0.400 1.814 scale MinMaxScaler() 0 -> 0.5396775357552911
3181/3780 0.400 1.814 auto StandardScaler() 0 -> 0.5392101057932472
3182/3780 0.400 1.814 auto MinMaxScaler() 0 -> 0.562208933043079
3183/3780 0.400 1.814 0.01 StandardScaler() 0 -> 0.5565425366009649
3184/3780 0.400 1.814 0.01 MinMaxScaler() 0 -> 0.5884811338260377
3185/3780 0.400 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5461019019581802
3186/3780 0.400 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5842728218455292
3187/3780 0.400 1.814 0.1 StandardScaler() 0 -> 0.5402606785624053
3188/3780 0.400 1.814 0.1 MinMaxScaler() 0 -> 0.5733305467479739
3189/3780 0.400 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5439005125256151
3190/3780 0.400 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.5559998660850934
3191/3780 0.400 1.814 1.0 StandardScaler() 0 -> 0.5485356331879501
3192/3780 0.400 1.814 1.0 MinMaxScaler() 0 -> 0.5449698303575138
3193/3780 0.400 2.302 scale StandardScaler() 0 -> 0.5402292361239053
3194/3780 0.400 2.302 scale MinMaxScaler() 0 -> 0.5404732898154517
3195/3780 0.400 2.302 auto StandardScaler() 0 -> 0.5402292361239049
3196/3780 0.400 2.302 auto MinMaxScaler() 0 -> 0.5604095732602025
3197/3780 0.400 2.302 0.01 StandardScaler() 0 -> 0.5548053132145542
3198/3780 0.400 2.302 0.01 MinMaxScaler() 0 -> 0.5871874955693014
3199/3780 0.400 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5451678046439773
3200/3780 0.400 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5835380597089602
3201/3780 0.400 2.302 0.1 StandardScaler() 0 -> 0.5401395380971671
3202/3780 0.400 2.302 0.1 MinMaxScaler() 0 -> 0.5712344158693915
3203/3780 0.400 2.302 0.31622776601683794 StandardScaler() 0 -> 0.54631488817517
3204/3780 0.400 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5547248266379435
3205/3780 0.400 2.302 1.0 StandardScaler() 0 -> 0.5529078182722094
3206/3780 0.400 2.302 1.0 MinMaxScaler() 0 -> 0.5436916790951265
3207/3780 0.400 2.921 scale StandardScaler() 0 -> 0.5415909018713108
3208/3780 0.400 2.921 scale MinMaxScaler() 0 -> 0.540856152647014
3209/3780 0.400 2.921 auto StandardScaler() 0 -> 0.54159090187131
3210/3780 0.400 2.921 auto MinMaxScaler() 0 -> 0.5585296561565906
3211/3780 0.400 2.921 0.01 StandardScaler() 0 -> 0.5534669061298937
3212/3780 0.400 2.921 0.01 MinMaxScaler() 0 -> 0.5866454663669091
3213/3780 0.400 2.921 0.03162277660168379 StandardScaler() 0 -> 0.5440933784946482
3214/3780 0.400 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5828562420753902
3215/3780 0.400 2.921 0.1 StandardScaler() 0 -> 0.5408371814491922
3216/3780 0.400 2.921 0.1 MinMaxScaler() 0 -> 0.5692476407002068
3217/3780 0.400 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5496504003857156
3218/3780 0.400 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5536376680900043
3219/3780 0.400 2.921 1.0 StandardScaler() 0 -> 0.5590898430394634
3220/3780 0.400 2.921 1.0 MinMaxScaler() 0 -> 0.5425272842250345
3221/3780 0.400 3.707 scale StandardScaler() 0 -> 0.543707637525476
3222/3780 0.400 3.707 scale MinMaxScaler() 0 -> 0.5425071693685308
3223/3780 0.400 3.707 auto StandardScaler() 0 -> 0.5437076375254768
3224/3780 0.400 3.707 auto MinMaxScaler() 0 -> 0.5570927616313949
3225/3780 0.400 3.707 0.01 StandardScaler() 0 -> 0.5529980233019608
3226/3780 0.400 3.707 0.01 MinMaxScaler() 0 -> 0.5862627293294148
3227/3780 0.400 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5431444633067121
3228/3780 0.400 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5820824435423954
3229/3780 0.400 3.707 0.1 StandardScaler() 0 -> 0.5415264077915087
3230/3780 0.400 3.707 0.1 MinMaxScaler() 0 -> 0.5672438180976802
3231/3780 0.400 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5536557834257522
3232/3780 0.400 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5532513617627318
3233/3780 0.400 3.707 1.0 StandardScaler() 0 -> 0.5670642829157203
3234/3780 0.400 3.707 1.0 MinMaxScaler() 0 -> 0.5415466276460307
3235/3780 0.400 4.703 scale StandardScaler() 0 -> 0.5461367473509177
3236/3780 0.400 4.703 scale MinMaxScaler() 0 -> 0.5444749999223731
3237/3780 0.400 4.703 auto StandardScaler() 0 -> 0.546136747350915
3238/3780 0.400 4.703 auto MinMaxScaler() 0 -> 0.5554172362031701
3239/3780 0.400 4.703 0.01 StandardScaler() 0 -> 0.5521311101403034
3240/3780 0.400 4.703 0.01 MinMaxScaler() 0 -> 0.5857778922967506
3241/3780 0.400 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5422376610784593
3242/3780 0.400 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5811146274103725
3243/3780 0.400 4.703 0.1 StandardScaler() 0 -> 0.5420909957402211
3244/3780 0.400 4.703 0.1 MinMaxScaler() 0 -> 0.5652359406138313
3245/3780 0.400 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5574886791748308
3246/3780 0.400 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5528623026659901
3247/3780 0.400 4.703 1.0 StandardScaler() 0 -> 0.5777794009469766
3248/3780 0.400 4.703 1.0 MinMaxScaler() 0 -> 0.5411898555829519
3249/3780 0.400 5.968 scale StandardScaler() 0 -> 0.5496822007037538
3250/3780 0.400 5.968 scale MinMaxScaler() 0 -> 0.5467570828647909
3251/3780 0.400 5.968 auto StandardScaler() 0 -> 0.5496822007037535
3252/3780 0.400 5.968 auto MinMaxScaler() 0 -> 0.554628229067624
3253/3780 0.400 5.968 0.01 StandardScaler() 0 -> 0.5516751775313998
3254/3780 0.400 5.968 0.01 MinMaxScaler() 0 -> 0.5854569753534943
3255/3780 0.400 5.968 0.03162277660168379 StandardScaler() 0 -> 0.541477335317595
3256/3780 0.400 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5801068381417567
3257/3780 0.400 5.968 0.1 StandardScaler() 0 -> 0.542249479375124
3258/3780 0.400 5.968 0.1 MinMaxScaler() 0 -> 0.5635879233637565
3259/3780 0.400 5.968 0.31622776601683794 StandardScaler() 0 -> 0.561556972017719
3260/3780 0.400 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5523388498618681
3261/3780 0.400 5.968 1.0 StandardScaler() 0 -> 0.5892344775881782
3262/3780 0.400 5.968 1.0 MinMaxScaler() 0 -> 0.5410961308824067
3263/3780 0.400 7.574 scale StandardScaler() 0 -> 0.5555899037826587
3264/3780 0.400 7.574 scale MinMaxScaler() 0 -> 0.5506745912856043
3265/3780 0.400 7.574 auto StandardScaler() 0 -> 0.5555899037826576
3266/3780 0.400 7.574 auto MinMaxScaler() 0 -> 0.5537095102348161
3267/3780 0.400 7.574 0.01 StandardScaler() 0 -> 0.5514727261577983
3268/3780 0.400 7.574 0.01 MinMaxScaler() 0 -> 0.5850762791035135
3269/3780 0.400 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5411273013753927
3270/3780 0.400 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5789777959910778
3271/3780 0.400 7.574 0.1 StandardScaler() 0 -> 0.5435283499982299
3272/3780 0.400 7.574 0.1 MinMaxScaler() 0 -> 0.5617322733953904
3273/3780 0.400 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5656319828978943
3274/3780 0.400 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5515314925598708
3275/3780 0.400 7.574 1.0 StandardScaler() 0 -> 0.6012604790685941
3276/3780 0.400 7.574 1.0 MinMaxScaler() 0 -> 0.5409528103122447
3277/3780 0.400 9.611 scale StandardScaler() 0 -> 0.5620255850810753
3278/3780 0.400 9.611 scale MinMaxScaler() 0 -> 0.556718426209959
3279/3780 0.400 9.611 auto StandardScaler() 0 -> 0.5620255850810695
3280/3780 0.400 9.611 auto MinMaxScaler() 0 -> 0.5536096480775377
3281/3780 0.400 9.611 0.01 StandardScaler() 0 -> 0.5508744548596333
3282/3780 0.400 9.611 0.01 MinMaxScaler() 0 -> 0.584668618453704
3283/3780 0.400 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5405480729819789
3284/3780 0.400 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5775472395989812
3285/3780 0.400 9.611 0.1 StandardScaler() 0 -> 0.5452497468184463
3286/3780 0.400 9.611 0.1 MinMaxScaler() 0 -> 0.5599429030325823
3287/3780 0.400 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5709086626607002
3288/3780 0.400 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.5504806011226303
3289/3780 0.400 9.611 1.0 StandardScaler() 0 -> 0.6138200782222983
3290/3780 0.400 9.611 1.0 MinMaxScaler() 0 -> 0.5403671053352467
3291/3780 0.400 12.196 scale StandardScaler() 0 -> 0.5685085438097613
3292/3780 0.400 12.196 scale MinMaxScaler() 0 -> 0.56084797616615
3293/3780 0.400 12.196 auto StandardScaler() 0 -> 0.5685085438097617
3294/3780 0.400 12.196 auto MinMaxScaler() 0 -> 0.5533290972420365
3295/3780 0.400 12.196 0.01 StandardScaler() 0 -> 0.5503653573217435
3296/3780 0.400 12.196 0.01 MinMaxScaler() 0 -> 0.5843446897585002
3297/3780 0.400 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5393780949131926
3298/3780 0.400 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5758205307535614
3299/3780 0.400 12.196 0.1 StandardScaler() 0 -> 0.5465236605466018
3300/3780 0.400 12.196 0.1 MinMaxScaler() 0 -> 0.5580560843257891
3301/3780 0.400 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5769792299227522
3302/3780 0.400 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5496529246753269
3303/3780 0.400 12.196 1.0 StandardScaler() 0 -> 0.6265100279158307
3304/3780 0.400 12.196 1.0 MinMaxScaler() 0 -> 0.5407816152398146
3305/3780 0.400 15.476 scale StandardScaler() 0 -> 0.5730378053674847
3306/3780 0.400 15.476 scale MinMaxScaler() 0 -> 0.5652855515220562
3307/3780 0.400 15.476 auto StandardScaler() 0 -> 0.5730378053674873
3308/3780 0.400 15.476 auto MinMaxScaler() 0 -> 0.5533489869356777
3309/3780 0.400 15.476 0.01 StandardScaler() 0 -> 0.5502124331521183
3310/3780 0.400 15.476 0.01 MinMaxScaler() 0 -> 0.5840196341553944
3311/3780 0.400 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5394528469119425
3312/3780 0.400 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5742540862518679
3313/3780 0.400 15.476 0.1 StandardScaler() 0 -> 0.547005220113372
3314/3780 0.400 15.476 0.1 MinMaxScaler() 0 -> 0.5569862170383605
3315/3780 0.400 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5832979366384419
3316/3780 0.400 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5491771832054432
3317/3780 0.400 15.476 1.0 StandardScaler() 0 -> 0.640544989282183
3318/3780 0.400 15.476 1.0 MinMaxScaler() 0 -> 0.5409692416586643
3319/3780 0.400 19.638 scale StandardScaler() 0 -> 0.5765247892740496
3320/3780 0.400 19.638 scale MinMaxScaler() 0 -> 0.5693309043428241
3321/3780 0.400 19.638 auto StandardScaler() 0 -> 0.5765247892740439
3322/3780 0.400 19.638 auto MinMaxScaler() 0 -> 0.5528711982014606
3323/3780 0.400 19.638 0.01 StandardScaler() 0 -> 0.5502481823485825
3324/3780 0.400 19.638 0.01 MinMaxScaler() 0 -> 0.5835732047820493
3325/3780 0.400 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5395993215617192
3326/3780 0.400 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.572197827950521
3327/3780 0.400 19.638 0.1 StandardScaler() 0 -> 0.5485559716638343
3328/3780 0.400 19.638 0.1 MinMaxScaler() 0 -> 0.5555337590225138
3329/3780 0.400 19.638 0.31622776601683794 StandardScaler() 0 -> 0.592481088781511
3330/3780 0.400 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5480744959465341
3331/3780 0.400 19.638 1.0 StandardScaler() 0 -> 0.6561817427096489
3332/3780 0.400 19.638 1.0 MinMaxScaler() 0 -> 0.5410607692918993
3333/3780 0.400 24.920 scale StandardScaler() 0 -> 0.5806426954337772
3334/3780 0.400 24.920 scale MinMaxScaler() 0 -> 0.5730635375572882
3335/3780 0.400 24.920 auto StandardScaler() 0 -> 0.580642695433785
3336/3780 0.400 24.920 auto MinMaxScaler() 0 -> 0.5521124563766915
3337/3780 0.400 24.920 0.01 StandardScaler() 0 -> 0.5497910765010309
3338/3780 0.400 24.920 0.01 MinMaxScaler() 0 -> 0.5829002077296229
3339/3780 0.400 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5394505531193658
3340/3780 0.400 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5702276575410271
3341/3780 0.400 24.920 0.1 StandardScaler() 0 -> 0.5506781770550324
3342/3780 0.400 24.920 0.1 MinMaxScaler() 0 -> 0.5546283863146776
3343/3780 0.400 24.920 0.31622776601683794 StandardScaler() 0 -> 0.6026303990971171
3344/3780 0.400 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5473505505367064
3345/3780 0.400 24.920 1.0 StandardScaler() 0 -> 0.6764835146967317
3346/3780 0.400 24.920 1.0 MinMaxScaler() 0 -> 0.5409728560505308
3347/3780 0.400 31.623 scale StandardScaler() 0 -> 0.5853046402512914
3348/3780 0.400 31.623 scale MinMaxScaler() 0 -> 0.5781081138263654
3349/3780 0.400 31.623 auto StandardScaler() 0 -> 0.5853046402512949
3350/3780 0.400 31.623 auto MinMaxScaler() 0 -> 0.5511893158106195
3351/3780 0.400 31.623 0.01 StandardScaler() 0 -> 0.5494915513191218
3352/3780 0.400 31.623 0.01 MinMaxScaler() 0 -> 0.582290108228571
3353/3780 0.400 31.623 0.03162277660168379 StandardScaler() 0 -> 0.5397826584326526
3354/3780 0.400 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5685087249372138
3355/3780 0.400 31.623 0.1 StandardScaler() 0 -> 0.5538216601123248
3356/3780 0.400 31.623 0.1 MinMaxScaler() 0 -> 0.5543314526203642
3357/3780 0.400 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6129336321560701
3358/3780 0.400 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5463919614311026
3359/3780 0.400 31.623 1.0 StandardScaler() 0 -> 0.7011252482213971
3360/3780 0.400 31.623 1.0 MinMaxScaler() 0 -> 0.5411819330956611
3361/3780 0.450 0.032 scale StandardScaler() 0 -> 0.5714651302600123
3362/3780 0.450 0.032 scale MinMaxScaler() 0 -> 0.5707238226169635
3363/3780 0.450 0.032 auto StandardScaler() 0 -> 0.5714651302600123
3364/3780 0.450 0.032 auto MinMaxScaler() 0 -> 0.6132988108228727
3365/3780 0.450 0.032 0.01 StandardScaler() 0 -> 0.6102899998608655
3366/3780 0.450 0.032 0.01 MinMaxScaler() 0 -> 0.8646015255634668
3367/3780 0.450 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5813929882083022
3368/3780 0.450 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.8183070124908146
3369/3780 0.450 0.032 0.1 StandardScaler() 0 -> 0.569153788303223
3370/3780 0.450 0.032 0.1 MinMaxScaler() 0 -> 0.7034401359535994
3371/3780 0.450 0.032 0.31622776601683794 StandardScaler() 0 -> 0.5774435986357157
3372/3780 0.450 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5950943583314368
3373/3780 0.450 0.032 1.0 StandardScaler() 0 -> 0.6472980604890991
3374/3780 0.450 0.032 1.0 MinMaxScaler() 0 -> 0.578044947587919
3375/3780 0.450 0.040 scale StandardScaler() 0 -> 0.5688233973193741
3376/3780 0.450 0.040 scale MinMaxScaler() 0 -> 0.5678823189289571
3377/3780 0.450 0.040 auto StandardScaler() 0 -> 0.568823397319374
3378/3780 0.450 0.040 auto MinMaxScaler() 0 -> 0.5997016016032353
3379/3780 0.450 0.040 0.01 StandardScaler() 0 -> 0.597036583795885
3380/3780 0.450 0.040 0.01 MinMaxScaler() 0 -> 0.8585464658527465
3381/3780 0.450 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5784046606484834
3382/3780 0.450 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.8012291243040801
3383/3780 0.450 0.040 0.1 StandardScaler() 0 -> 0.5665946072778019
3384/3780 0.450 0.040 0.1 MinMaxScaler() 0 -> 0.6683600889946447
3385/3780 0.450 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5727151367255455
3386/3780 0.450 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5909259123858118
3387/3780 0.450 0.040 1.0 StandardScaler() 0 -> 0.6244044554204665
3388/3780 0.450 0.040 1.0 MinMaxScaler() 0 -> 0.5757035389317169
3389/3780 0.450 0.051 scale StandardScaler() 0 -> 0.5652107395388501
3390/3780 0.450 0.051 scale MinMaxScaler() 0 -> 0.565856432190706
3391/3780 0.450 0.051 auto StandardScaler() 0 -> 0.5652107395388501
3392/3780 0.450 0.051 auto MinMaxScaler() 0 -> 0.5944043515883681
3393/3780 0.450 0.051 0.01 StandardScaler() 0 -> 0.5918138214510305
3394/3780 0.450 0.051 0.01 MinMaxScaler() 0 -> 0.8509558587978344
3395/3780 0.450 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5754012838081851
3396/3780 0.450 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.780697467514219
3397/3780 0.450 0.051 0.1 StandardScaler() 0 -> 0.5645922201804288
3398/3780 0.450 0.051 0.1 MinMaxScaler() 0 -> 0.6340254551064285
3399/3780 0.450 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5681532677500901
3400/3780 0.450 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5882468102343329
3401/3780 0.450 0.051 1.0 StandardScaler() 0 -> 0.6065433179608785
3402/3780 0.450 0.051 1.0 MinMaxScaler() 0 -> 0.5737711626215037
3403/3780 0.450 0.065 scale StandardScaler() 0 -> 0.5627434854200778
3404/3780 0.450 0.065 scale MinMaxScaler() 0 -> 0.5636661261708912
3405/3780 0.450 0.065 auto StandardScaler() 0 -> 0.5627434854200778
3406/3780 0.450 0.065 auto MinMaxScaler() 0 -> 0.5910955081659715
3407/3780 0.450 0.065 0.01 StandardScaler() 0 -> 0.5888852380369242
3408/3780 0.450 0.065 0.01 MinMaxScaler() 0 -> 0.8414825530345812
3409/3780 0.450 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5727341182328934
3410/3780 0.450 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.7564800227244483
3411/3780 0.450 0.065 0.1 StandardScaler() 0 -> 0.5625103249663876
3412/3780 0.450 0.065 0.1 MinMaxScaler() 0 -> 0.6092129600356513
3413/3780 0.450 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5639136151297294
3414/3780 0.450 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5859812425718834
3415/3780 0.450 0.065 1.0 StandardScaler() 0 -> 0.5934084850130682
3416/3780 0.450 0.065 1.0 MinMaxScaler() 0 -> 0.5710222178484193
3417/3780 0.450 0.082 scale StandardScaler() 0 -> 0.5598716919367442
3418/3780 0.450 0.082 scale MinMaxScaler() 0 -> 0.5614023259144963
3419/3780 0.450 0.082 auto StandardScaler() 0 -> 0.5598716919367442
3420/3780 0.450 0.082 auto MinMaxScaler() 0 -> 0.5889207196538839
3421/3780 0.450 0.082 0.01 StandardScaler() 0 -> 0.5863934755689214
3422/3780 0.450 0.082 0.01 MinMaxScaler() 0 -> 0.8296500192202018
3423/3780 0.450 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5698071542156692
3424/3780 0.450 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.7268660984737743
3425/3780 0.450 0.082 0.1 StandardScaler() 0 -> 0.5606457136065841
3426/3780 0.450 0.082 0.1 MinMaxScaler() 0 -> 0.599148507826449
3427/3780 0.450 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5607727024266239
3428/3780 0.450 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.583274264006869
3429/3780 0.450 0.082 1.0 StandardScaler() 0 -> 0.5846640705056584
3430/3780 0.450 0.082 1.0 MinMaxScaler() 0 -> 0.5687091188826786
3431/3780 0.450 0.104 scale StandardScaler() 0 -> 0.5574893888894258
3432/3780 0.450 0.104 scale MinMaxScaler() 0 -> 0.5597096517916156
3433/3780 0.450 0.104 auto StandardScaler() 0 -> 0.5574893888894258
3434/3780 0.450 0.104 auto MinMaxScaler() 0 -> 0.586707877945848
3435/3780 0.450 0.104 0.01 StandardScaler() 0 -> 0.5839567875038584
3436/3780 0.450 0.104 0.01 MinMaxScaler() 0 -> 0.8151158104164252
3437/3780 0.450 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5675096928831432
3438/3780 0.450 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6940711634266871
3439/3780 0.450 0.104 0.1 StandardScaler() 0 -> 0.5594883490566002
3440/3780 0.450 0.104 0.1 MinMaxScaler() 0 -> 0.5941221760892818
3441/3780 0.450 0.104 0.31622776601683794 StandardScaler() 0 -> 0.556958779527489
3442/3780 0.450 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5809804056420366
3443/3780 0.450 0.104 1.0 StandardScaler() 0 -> 0.5757320425301086
3444/3780 0.450 0.104 1.0 MinMaxScaler() 0 -> 0.5666134681185442
3445/3780 0.450 0.132 scale StandardScaler() 0 -> 0.5552209557187907
3446/3780 0.450 0.132 scale MinMaxScaler() 0 -> 0.5575798354333896
3447/3780 0.450 0.132 auto StandardScaler() 0 -> 0.5552209557187906
3448/3780 0.450 0.132 auto MinMaxScaler() 0 -> 0.5848624427805493
3449/3780 0.450 0.132 0.01 StandardScaler() 0 -> 0.5815904643392912
3450/3780 0.450 0.132 0.01 MinMaxScaler() 0 -> 0.797440277051218
3451/3780 0.450 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5655652960179359
3452/3780 0.450 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6587123398852625
3453/3780 0.450 0.132 0.1 StandardScaler() 0 -> 0.558352404667581
3454/3780 0.450 0.132 0.1 MinMaxScaler() 0 -> 0.5916162346270406
3455/3780 0.450 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5538093987190459
3456/3780 0.450 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5789747223865956
3457/3780 0.450 0.132 1.0 StandardScaler() 0 -> 0.5690169440896765
3458/3780 0.450 0.132 1.0 MinMaxScaler() 0 -> 0.5646548751050885
3459/3780 0.450 0.168 scale StandardScaler() 0 -> 0.5527532196560596
3460/3780 0.450 0.168 scale MinMaxScaler() 0 -> 0.5554968159825181
3461/3780 0.450 0.168 auto StandardScaler() 0 -> 0.5527532196560595
3462/3780 0.450 0.168 auto MinMaxScaler() 0 -> 0.5825305591533647
3463/3780 0.450 0.168 0.01 StandardScaler() 0 -> 0.5796132772374628
3464/3780 0.450 0.168 0.01 MinMaxScaler() 0 -> 0.7761492958276043
3465/3780 0.450 0.168 0.03162277660168379 StandardScaler() 0 -> 0.563204394473879
3466/3780 0.450 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6253662670541843
3467/3780 0.450 0.168 0.1 StandardScaler() 0 -> 0.5562219565531676
3468/3780 0.450 0.168 0.1 MinMaxScaler() 0 -> 0.5893654247131345
3469/3780 0.450 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5521021821665548
3470/3780 0.450 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5770244272925313
3471/3780 0.450 0.168 1.0 StandardScaler() 0 -> 0.5629109155638679
3472/3780 0.450 0.168 1.0 MinMaxScaler() 0 -> 0.562780091217341
3473/3780 0.450 0.213 scale StandardScaler() 0 -> 0.5505072336231108
3474/3780 0.450 0.213 scale MinMaxScaler() 0 -> 0.5531947852032503
3475/3780 0.450 0.213 auto StandardScaler() 0 -> 0.5505072336231107
3476/3780 0.450 0.213 auto MinMaxScaler() 0 -> 0.580683928380969
3477/3780 0.450 0.213 0.01 StandardScaler() 0 -> 0.5773612580008622
3478/3780 0.450 0.213 0.01 MinMaxScaler() 0 -> 0.7509435055791572
3479/3780 0.450 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5609438690613845
3480/3780 0.450 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6058578240134603
3481/3780 0.450 0.213 0.1 StandardScaler() 0 -> 0.5549837576415491
3482/3780 0.450 0.213 0.1 MinMaxScaler() 0 -> 0.5876971911521102
3483/3780 0.450 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5504053983729533
3484/3780 0.450 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5750420033066518
3485/3780 0.450 0.213 1.0 StandardScaler() 0 -> 0.5576116537592807
3486/3780 0.450 0.213 1.0 MinMaxScaler() 0 -> 0.5611756485204289
3487/3780 0.450 0.270 scale StandardScaler() 0 -> 0.5488916645841647
3488/3780 0.450 0.270 scale MinMaxScaler() 0 -> 0.550686972480178
3489/3780 0.450 0.270 auto StandardScaler() 0 -> 0.5488916645841646
3490/3780 0.450 0.270 auto MinMaxScaler() 0 -> 0.5791344709404443
3491/3780 0.450 0.270 0.01 StandardScaler() 0 -> 0.5751995286232284
3492/3780 0.450 0.270 0.01 MinMaxScaler() 0 -> 0.7207221011041652
3493/3780 0.450 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5591107933727978
3494/3780 0.450 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5981391673018494
3495/3780 0.450 0.270 0.1 StandardScaler() 0 -> 0.5534488968182156
3496/3780 0.450 0.270 0.1 MinMaxScaler() 0 -> 0.5861531792693108
3497/3780 0.450 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5488158487831171
3498/3780 0.450 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5730431924041633
3499/3780 0.450 0.270 1.0 StandardScaler() 0 -> 0.5539957570549026
3500/3780 0.450 0.270 1.0 MinMaxScaler() 0 -> 0.5602069417265149
3501/3780 0.450 0.342 scale StandardScaler() 0 -> 0.5478412214220019
3502/3780 0.450 0.342 scale MinMaxScaler() 0 -> 0.5492448154830473
3503/3780 0.450 0.342 auto StandardScaler() 0 -> 0.5478412214220016
3504/3780 0.450 0.342 auto MinMaxScaler() 0 -> 0.5775049181188942
3505/3780 0.450 0.342 0.01 StandardScaler() 0 -> 0.5733092126864519
3506/3780 0.450 0.342 0.01 MinMaxScaler() 0 -> 0.6865901278427607
3507/3780 0.450 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5578199586686324
3508/3780 0.450 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5938457094536109
3509/3780 0.450 0.342 0.1 StandardScaler() 0 -> 0.5516470757008566
3510/3780 0.450 0.342 0.1 MinMaxScaler() 0 -> 0.5845086474129809
3511/3780 0.450 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5473377291874875
3512/3780 0.450 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5707322946432817
3513/3780 0.450 0.342 1.0 StandardScaler() 0 -> 0.550580289282598
3514/3780 0.450 0.342 1.0 MinMaxScaler() 0 -> 0.559653864958069
3515/3780 0.450 0.434 scale StandardScaler() 0 -> 0.54592288014466
3516/3780 0.450 0.434 scale MinMaxScaler() 0 -> 0.5477656397129956
3517/3780 0.450 0.434 auto StandardScaler() 0 -> 0.54592288014466
3518/3780 0.450 0.434 auto MinMaxScaler() 0 -> 0.5754560699087866
3519/3780 0.450 0.434 0.01 StandardScaler() 0 -> 0.5711769810163511
3520/3780 0.450 0.434 0.01 MinMaxScaler() 0 -> 0.6519331138800042
3521/3780 0.450 0.434 0.03162277660168379 StandardScaler() 0 -> 0.5571661483169218
3522/3780 0.450 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5918243020600794
3523/3780 0.450 0.434 0.1 StandardScaler() 0 -> 0.5499483762663422
3524/3780 0.450 0.434 0.1 MinMaxScaler() 0 -> 0.5831292106466851
3525/3780 0.450 0.434 0.31622776601683794 StandardScaler() 0 -> 0.5455001369389166
3526/3780 0.450 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5689964866170437
3527/3780 0.450 0.434 1.0 StandardScaler() 0 -> 0.5480615176432723
3528/3780 0.450 0.434 1.0 MinMaxScaler() 0 -> 0.559000895629247
3529/3780 0.450 0.551 scale StandardScaler() 0 -> 0.5447928218044089
3530/3780 0.450 0.551 scale MinMaxScaler() 0 -> 0.5464595504209453
3531/3780 0.450 0.551 auto StandardScaler() 0 -> 0.5447928218044086
3532/3780 0.450 0.551 auto MinMaxScaler() 0 -> 0.5737007370314774
3533/3780 0.450 0.551 0.01 StandardScaler() 0 -> 0.5690181002560598
3534/3780 0.450 0.551 0.01 MinMaxScaler() 0 -> 0.620432081164441
3535/3780 0.450 0.551 0.03162277660168379 StandardScaler() 0 -> 0.5564769501063461
3536/3780 0.450 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5898802136740623
3537/3780 0.450 0.551 0.1 StandardScaler() 0 -> 0.5492177197704051
3538/3780 0.450 0.551 0.1 MinMaxScaler() 0 -> 0.5819046018009577
3539/3780 0.450 0.551 0.31622776601683794 StandardScaler() 0 -> 0.5437887494055335
3540/3780 0.450 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5674561545951278
3541/3780 0.450 0.551 1.0 StandardScaler() 0 -> 0.5462201323704924
3542/3780 0.450 0.551 1.0 MinMaxScaler() 0 -> 0.5584096961864654
3543/3780 0.450 0.700 scale StandardScaler() 0 -> 0.5439815499836643
3544/3780 0.450 0.700 scale MinMaxScaler() 0 -> 0.545250931703893
3545/3780 0.450 0.700 auto StandardScaler() 0 -> 0.543981549983664
3546/3780 0.450 0.700 auto MinMaxScaler() 0 -> 0.5716781596842627
3547/3780 0.450 0.700 0.01 StandardScaler() 0 -> 0.5674760478187837
3548/3780 0.450 0.700 0.01 MinMaxScaler() 0 -> 0.603029970652167
3549/3780 0.450 0.700 0.03162277660168379 StandardScaler() 0 -> 0.5564769133699422
3550/3780 0.450 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5883410187495048
3551/3780 0.450 0.700 0.1 StandardScaler() 0 -> 0.5471426988356427
3552/3780 0.450 0.700 0.1 MinMaxScaler() 0 -> 0.580612336076044
3553/3780 0.450 0.700 0.31622776601683794 StandardScaler() 0 -> 0.5424540432813508
3554/3780 0.450 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5660890897271244
3555/3780 0.450 0.700 1.0 StandardScaler() 0 -> 0.5450007267480649
3556/3780 0.450 0.700 1.0 MinMaxScaler() 0 -> 0.5571189476344434
3557/3780 0.450 0.888 scale StandardScaler() 0 -> 0.5436952146819952
3558/3780 0.450 0.888 scale MinMaxScaler() 0 -> 0.5446893185955358
3559/3780 0.450 0.888 auto StandardScaler() 0 -> 0.5436952146819952
3560/3780 0.450 0.888 auto MinMaxScaler() 0 -> 0.5699984810832739
3561/3780 0.450 0.888 0.01 StandardScaler() 0 -> 0.5650202266507746
3562/3780 0.450 0.888 0.01 MinMaxScaler() 0 -> 0.5976411952409394
3563/3780 0.450 0.888 0.03162277660168379 StandardScaler() 0 -> 0.5553478659488049
3564/3780 0.450 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5873556187455087
3565/3780 0.450 0.888 0.1 StandardScaler() 0 -> 0.5459421078346716
3566/3780 0.450 0.888 0.1 MinMaxScaler() 0 -> 0.5790701884927086
3567/3780 0.450 0.888 0.31622776601683794 StandardScaler() 0 -> 0.5422840664464271
3568/3780 0.450 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5643870581787928
3569/3780 0.450 0.888 1.0 StandardScaler() 0 -> 0.5438703011654358
3570/3780 0.450 0.888 1.0 MinMaxScaler() 0 -> 0.556243155761857
3571/3780 0.450 1.126 scale StandardScaler() 0 -> 0.5429594448268732
3572/3780 0.450 1.126 scale MinMaxScaler() 0 -> 0.5449092930985056
3573/3780 0.450 1.126 auto StandardScaler() 0 -> 0.5429594448268725
3574/3780 0.450 1.126 auto MinMaxScaler() 0 -> 0.5682110432001698
3575/3780 0.450 1.126 0.01 StandardScaler() 0 -> 0.5629130903799116
3576/3780 0.450 1.126 0.01 MinMaxScaler() 0 -> 0.5933360380400426
3577/3780 0.450 1.126 0.03162277660168379 StandardScaler() 0 -> 0.5550914013057715
3578/3780 0.450 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5859384941928689
3579/3780 0.450 1.126 0.1 StandardScaler() 0 -> 0.5459879813500448
3580/3780 0.450 1.126 0.1 MinMaxScaler() 0 -> 0.5773628038422701
3581/3780 0.450 1.126 0.31622776601683794 StandardScaler() 0 -> 0.542636015484537
3582/3780 0.450 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5629677617845
3583/3780 0.450 1.126 1.0 StandardScaler() 0 -> 0.5439568480558511
3584/3780 0.450 1.126 1.0 MinMaxScaler() 0 -> 0.5557008216575384
3585/3780 0.450 1.429 scale StandardScaler() 0 -> 0.5423874007288841
3586/3780 0.450 1.429 scale MinMaxScaler() 0 -> 0.5454044540522299
3587/3780 0.450 1.429 auto StandardScaler() 0 -> 0.5423874007288841
3588/3780 0.450 1.429 auto MinMaxScaler() 0 -> 0.5668001592082277
3589/3780 0.450 1.429 0.01 StandardScaler() 0 -> 0.5609523010925617
3590/3780 0.450 1.429 0.01 MinMaxScaler() 0 -> 0.5917104442980442
3591/3780 0.450 1.429 0.03162277660168379 StandardScaler() 0 -> 0.5543154107794593
3592/3780 0.450 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5852608064203273
3593/3780 0.450 1.429 0.1 StandardScaler() 0 -> 0.5451295420906709
3594/3780 0.450 1.429 0.1 MinMaxScaler() 0 -> 0.575974279332239
3595/3780 0.450 1.429 0.31622776601683794 StandardScaler() 0 -> 0.5437190083885554
3596/3780 0.450 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.562461335645695
3597/3780 0.450 1.429 1.0 StandardScaler() 0 -> 0.5456854235879455
3598/3780 0.450 1.429 1.0 MinMaxScaler() 0 -> 0.5545676102820226
3599/3780 0.450 1.814 scale StandardScaler() 0 -> 0.5429598446198451
3600/3780 0.450 1.814 scale MinMaxScaler() 0 -> 0.5451663685477421
3601/3780 0.450 1.814 auto StandardScaler() 0 -> 0.5429598446198441
3602/3780 0.450 1.814 auto MinMaxScaler() 0 -> 0.5651683505204349
3603/3780 0.450 1.814 0.01 StandardScaler() 0 -> 0.5599809689984289
3604/3780 0.450 1.814 0.01 MinMaxScaler() 0 -> 0.5899921448132934
3605/3780 0.450 1.814 0.03162277660168379 StandardScaler() 0 -> 0.5534826234247373
3606/3780 0.450 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5845269676651559
3607/3780 0.450 1.814 0.1 StandardScaler() 0 -> 0.544444582441883
3608/3780 0.450 1.814 0.1 MinMaxScaler() 0 -> 0.5744349394858913
3609/3780 0.450 1.814 0.31622776601683794 StandardScaler() 0 -> 0.5462170506595041
3610/3780 0.450 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.56223804117743
3611/3780 0.450 1.814 1.0 StandardScaler() 0 -> 0.5481415240351052
3612/3780 0.450 1.814 1.0 MinMaxScaler() 0 -> 0.5532362512709255
3613/3780 0.450 2.302 scale StandardScaler() 0 -> 0.543435972157469
3614/3780 0.450 2.302 scale MinMaxScaler() 0 -> 0.5451818089404356
3615/3780 0.450 2.302 auto StandardScaler() 0 -> 0.543435972157469
3616/3780 0.450 2.302 auto MinMaxScaler() 0 -> 0.5634472015694968
3617/3780 0.450 2.302 0.01 StandardScaler() 0 -> 0.5590498526223914
3618/3780 0.450 2.302 0.01 MinMaxScaler() 0 -> 0.5885940987705452
3619/3780 0.450 2.302 0.03162277660168379 StandardScaler() 0 -> 0.5528114039785499
3620/3780 0.450 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5839539984027388
3621/3780 0.450 2.302 0.1 StandardScaler() 0 -> 0.5440580275274963
3622/3780 0.450 2.302 0.1 MinMaxScaler() 0 -> 0.5726168313546206
3623/3780 0.450 2.302 0.31622776601683794 StandardScaler() 0 -> 0.5492769944138809
3624/3780 0.450 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.5619791385671993
3625/3780 0.450 2.302 1.0 StandardScaler() 0 -> 0.551890832673083
3626/3780 0.450 2.302 1.0 MinMaxScaler() 0 -> 0.5520039926995725
3627/3780 0.450 2.921 scale StandardScaler() 0 -> 0.5448327068335826
3628/3780 0.450 2.921 scale MinMaxScaler() 0 -> 0.5453445080271176
3629/3780 0.450 2.921 auto StandardScaler() 0 -> 0.5448327068335818
3630/3780 0.450 2.921 auto MinMaxScaler() 0 -> 0.562649151782996
3631/3780 0.450 2.921 0.01 StandardScaler() 0 -> 0.5582784742541983
3632/3780 0.450 2.921 0.01 MinMaxScaler() 0 -> 0.5876835647937084
3633/3780 0.450 2.921 0.03162277660168379 StandardScaler() 0 -> 0.55141003479851
3634/3780 0.450 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5830924162293294
3635/3780 0.450 2.921 0.1 StandardScaler() 0 -> 0.544948277191511
3636/3780 0.450 2.921 0.1 MinMaxScaler() 0 -> 0.5709097699111232
3637/3780 0.450 2.921 0.31622776601683794 StandardScaler() 0 -> 0.5522207634362207
3638/3780 0.450 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.5616094969515371
3639/3780 0.450 2.921 1.0 StandardScaler() 0 -> 0.5583027640951658
3640/3780 0.450 2.921 1.0 MinMaxScaler() 0 -> 0.5506050208224204
3641/3780 0.450 3.707 scale StandardScaler() 0 -> 0.5475121180304344
3642/3780 0.450 3.707 scale MinMaxScaler() 0 -> 0.5463052786150856
3643/3780 0.450 3.707 auto StandardScaler() 0 -> 0.5475121180304345
3644/3780 0.450 3.707 auto MinMaxScaler() 0 -> 0.5625455432038614
3645/3780 0.450 3.707 0.01 StandardScaler() 0 -> 0.557885934432129
3646/3780 0.450 3.707 0.01 MinMaxScaler() 0 -> 0.5864962927808874
3647/3780 0.450 3.707 0.03162277660168379 StandardScaler() 0 -> 0.5498677955587042
3648/3780 0.450 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5821651068821493
3649/3780 0.450 3.707 0.1 StandardScaler() 0 -> 0.545668068186043
3650/3780 0.450 3.707 0.1 MinMaxScaler() 0 -> 0.5689755510543778
3651/3780 0.450 3.707 0.31622776601683794 StandardScaler() 0 -> 0.5552461351863421
3652/3780 0.450 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.5603858819993486
3653/3780 0.450 3.707 1.0 StandardScaler() 0 -> 0.5669598089015248
3654/3780 0.450 3.707 1.0 MinMaxScaler() 0 -> 0.5496369867578661
3655/3780 0.450 4.703 scale StandardScaler() 0 -> 0.5507583529664783
3656/3780 0.450 4.703 scale MinMaxScaler() 0 -> 0.5481696833243955
3657/3780 0.450 4.703 auto StandardScaler() 0 -> 0.550758352966476
3658/3780 0.450 4.703 auto MinMaxScaler() 0 -> 0.562578143017766
3659/3780 0.450 4.703 0.01 StandardScaler() 0 -> 0.5577449550379395
3660/3780 0.450 4.703 0.01 MinMaxScaler() 0 -> 0.5859742876924959
3661/3780 0.450 4.703 0.03162277660168379 StandardScaler() 0 -> 0.5487743889713185
3662/3780 0.450 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5813272235623657
3663/3780 0.450 4.703 0.1 StandardScaler() 0 -> 0.5459524441315995
3664/3780 0.450 4.703 0.1 MinMaxScaler() 0 -> 0.5672200903347643
3665/3780 0.450 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5582966248610676
3666/3780 0.450 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.5602626421560705
3667/3780 0.450 4.703 1.0 StandardScaler() 0 -> 0.5765509637933929
3668/3780 0.450 4.703 1.0 MinMaxScaler() 0 -> 0.5480959376230574
3669/3780 0.450 5.968 scale StandardScaler() 0 -> 0.5541618171714449
3670/3780 0.450 5.968 scale MinMaxScaler() 0 -> 0.5510972598191096
3671/3780 0.450 5.968 auto StandardScaler() 0 -> 0.5541618171714444
3672/3780 0.450 5.968 auto MinMaxScaler() 0 -> 0.5623876917797236
3673/3780 0.450 5.968 0.01 StandardScaler() 0 -> 0.5576871317984002
3674/3780 0.450 5.968 0.01 MinMaxScaler() 0 -> 0.5856119522856846
3675/3780 0.450 5.968 0.03162277660168379 StandardScaler() 0 -> 0.54800525116961
3676/3780 0.450 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5803171468754794
3677/3780 0.450 5.968 0.1 StandardScaler() 0 -> 0.5459600846497699
3678/3780 0.450 5.968 0.1 MinMaxScaler() 0 -> 0.5658258335049898
3679/3780 0.450 5.968 0.31622776601683794 StandardScaler() 0 -> 0.5617537443204453
3680/3780 0.450 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.5597987781436313
3681/3780 0.450 5.968 1.0 StandardScaler() 0 -> 0.5864802159420726
3682/3780 0.450 5.968 1.0 MinMaxScaler() 0 -> 0.5473972566733772
3683/3780 0.450 7.574 scale StandardScaler() 0 -> 0.5585573477543787
3684/3780 0.450 7.574 scale MinMaxScaler() 0 -> 0.5552962204640912
3685/3780 0.450 7.574 auto StandardScaler() 0 -> 0.5585573477543808
3686/3780 0.450 7.574 auto MinMaxScaler() 0 -> 0.5618367025678537
3687/3780 0.450 7.574 0.01 StandardScaler() 0 -> 0.5575386370152962
3688/3780 0.450 7.574 0.01 MinMaxScaler() 0 -> 0.5852363797080313
3689/3780 0.450 7.574 0.03162277660168379 StandardScaler() 0 -> 0.5468053523393452
3690/3780 0.450 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5791585290433571
3691/3780 0.450 7.574 0.1 StandardScaler() 0 -> 0.5467518750162409
3692/3780 0.450 7.574 0.1 MinMaxScaler() 0 -> 0.5643406176649823
3693/3780 0.450 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5656801788372338
3694/3780 0.450 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.5594338720789104
3695/3780 0.450 7.574 1.0 StandardScaler() 0 -> 0.5965234260091438
3696/3780 0.450 7.574 1.0 MinMaxScaler() 0 -> 0.5465471271461279
3697/3780 0.450 9.611 scale StandardScaler() 0 -> 0.563596183080897
3698/3780 0.450 9.611 scale MinMaxScaler() 0 -> 0.5601847786504808
3699/3780 0.450 9.611 auto StandardScaler() 0 -> 0.56359618308089
3700/3780 0.450 9.611 auto MinMaxScaler() 0 -> 0.5608023421041537
3701/3780 0.450 9.611 0.01 StandardScaler() 0 -> 0.5575135176422861
3702/3780 0.450 9.611 0.01 MinMaxScaler() 0 -> 0.5847569733615323
3703/3780 0.450 9.611 0.03162277660168379 StandardScaler() 0 -> 0.5457839394339453
3704/3780 0.450 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5777425501722324
3705/3780 0.450 9.611 0.1 StandardScaler() 0 -> 0.5474697934342169
3706/3780 0.450 9.611 0.1 MinMaxScaler() 0 -> 0.5630520611174634
3707/3780 0.450 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5713389915007326
3708/3780 0.450 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.559140692312977
3709/3780 0.450 9.611 1.0 StandardScaler() 0 -> 0.6078828981142764
3710/3780 0.450 9.611 1.0 MinMaxScaler() 0 -> 0.5454796798942358
3711/3780 0.450 12.196 scale StandardScaler() 0 -> 0.5688364802867946
3712/3780 0.450 12.196 scale MinMaxScaler() 0 -> 0.5633108156906921
3713/3780 0.450 12.196 auto StandardScaler() 0 -> 0.5688364802867922
3714/3780 0.450 12.196 auto MinMaxScaler() 0 -> 0.560703373262545
3715/3780 0.450 12.196 0.01 StandardScaler() 0 -> 0.5577484249085921
3716/3780 0.450 12.196 0.01 MinMaxScaler() 0 -> 0.5843679014156061
3717/3780 0.450 12.196 0.03162277660168379 StandardScaler() 0 -> 0.5444424885653952
3718/3780 0.450 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5763211881019248
3719/3780 0.450 12.196 0.1 StandardScaler() 0 -> 0.5494721337151272
3720/3780 0.450 12.196 0.1 MinMaxScaler() 0 -> 0.5629785924373599
3721/3780 0.450 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5763523225648216
3722/3780 0.450 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.5583966134159758
3723/3780 0.450 12.196 1.0 StandardScaler() 0 -> 0.6212727624959291
3724/3780 0.450 12.196 1.0 MinMaxScaler() 0 -> 0.5444642368105876
3725/3780 0.450 15.476 scale StandardScaler() 0 -> 0.5733033164494454
3726/3780 0.450 15.476 scale MinMaxScaler() 0 -> 0.5674413268991221
3727/3780 0.450 15.476 auto StandardScaler() 0 -> 0.5733033164494484
3728/3780 0.450 15.476 auto MinMaxScaler() 0 -> 0.560249762236104
3729/3780 0.450 15.476 0.01 StandardScaler() 0 -> 0.5573715892521881
3730/3780 0.450 15.476 0.01 MinMaxScaler() 0 -> 0.5838899255723936
3731/3780 0.450 15.476 0.03162277660168379 StandardScaler() 0 -> 0.5440157771947781
3732/3780 0.450 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5750302845811173
3733/3780 0.450 15.476 0.1 StandardScaler() 0 -> 0.5506146683204617
3734/3780 0.450 15.476 0.1 MinMaxScaler() 0 -> 0.5626183428206283
3735/3780 0.450 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5835099983581576
3736/3780 0.450 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.5573324587345111
3737/3780 0.450 15.476 1.0 StandardScaler() 0 -> 0.6346195598815724
3738/3780 0.450 15.476 1.0 MinMaxScaler() 0 -> 0.5445718567553791
3739/3780 0.450 19.638 scale StandardScaler() 0 -> 0.5768513151753445
3740/3780 0.450 19.638 scale MinMaxScaler() 0 -> 0.5718423098258514
3741/3780 0.450 19.638 auto StandardScaler() 0 -> 0.5768513151753395
3742/3780 0.450 19.638 auto MinMaxScaler() 0 -> 0.5605291971185746
3743/3780 0.450 19.638 0.01 StandardScaler() 0 -> 0.5565392702543411
3744/3780 0.450 19.638 0.01 MinMaxScaler() 0 -> 0.5835454529880969
3745/3780 0.450 19.638 0.03162277660168379 StandardScaler() 0 -> 0.5445337699513692
3746/3780 0.450 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5734891612555417
3747/3780 0.450 19.638 0.1 StandardScaler() 0 -> 0.5518713596880064
3748/3780 0.450 19.638 0.1 MinMaxScaler() 0 -> 0.5627588265716162
3749/3780 0.450 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5915550279499145
3750/3780 0.450 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.5559715687008727
3751/3780 0.450 19.638 1.0 StandardScaler() 0 -> 0.6496827685766331
3752/3780 0.450 19.638 1.0 MinMaxScaler() 0 -> 0.5448203832104305
3753/3780 0.450 24.920 scale StandardScaler() 0 -> 0.5812964962323778
3754/3780 0.450 24.920 scale MinMaxScaler() 0 -> 0.5760132901474299
3755/3780 0.450 24.920 auto StandardScaler() 0 -> 0.5812964962323844
3756/3780 0.450 24.920 auto MinMaxScaler() 0 -> 0.5600924663338381
3757/3780 0.450 24.920 0.01 StandardScaler() 0 -> 0.5563562094464509
3758/3780 0.450 24.920 0.01 MinMaxScaler() 0 -> 0.583026614024709
3759/3780 0.450 24.920 0.03162277660168379 StandardScaler() 0 -> 0.5452792994717074
3760/3780 0.450 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5719282693246536
3761/3780 0.450 24.920 0.1 StandardScaler() 0 -> 0.5548383667803573
3762/3780 0.450 24.920 0.1 MinMaxScaler() 0 -> 0.5626808507204112
3763/3780 0.450 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5992015403469909
3764/3780 0.450 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.5549660583697814
3765/3780 0.450 24.920 1.0 StandardScaler() 0 -> 0.6681777235388312
3766/3780 0.450 24.920 1.0 MinMaxScaler() 0 -> 0.5453766598926791
3767/3780 0.450 31.623 scale StandardScaler() 0 -> 0.5854843976370221
3768/3780 0.450 31.623 scale MinMaxScaler() 0 -> 0.5799803336571
3769/3780 0.450 31.623 auto StandardScaler() 0 -> 0.5854843976370324
3770/3780 0.450 31.623 auto MinMaxScaler() 0 -> 0.5597309257843411
3771/3780 0.450 31.623 0.01 StandardScaler() 0 -> 0.5556896605513687
3772/3780 0.450 31.623 0.01 MinMaxScaler() 0 -> 0.5824064160054465
3773/3780 0.450 31.623 0.03162277660168379 StandardScaler() 0 -> 0.545611606674775
3774/3780 0.450 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5700133773261334
3775/3780 0.450 31.623 0.1 StandardScaler() 0 -> 0.558663340475678
3776/3780 0.450 31.623 0.1 MinMaxScaler() 0 -> 0.5623679896766564
3777/3780 0.450 31.623 0.31622776601683794 StandardScaler() 0 -> 0.6084326378924043
3778/3780 0.450 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.5543549248759133
3779/3780 0.450 31.623 1.0 StandardScaler() 0 -> 0.68840512982178
3780/3780 0.450 31.623 1.0 MinMaxScaler() 0 -> 0.5453299134882204
Time Taken 9650.848s
train_df, test_df = get_datasets(logarithm=True, feature_selection=False)
X_train = train_df.drop("quality",axis=1).values
X_test = test_df.drop("quality",axis=1).values
y_train = train_df["quality"].values
y_test = test_df["quality"].values
# Avaliable Kernels are {‘linear’, ‘poly’, ‘rbf’, ‘sigmoid’}
train_config = SupportVectorRegressor_train(X_train,y_train,cross_validation=True, kernel = "rbf", test_for_professor = test_for_professor)
df = pd.DataFrame.from_dict(train_config)
df = df.sort_values(by=['mse_val'])
if not test_for_professor:
df.to_csv('results/train_conf_svr.csv',index=False)
1/3780 0.050 0.032 scale StandardScaler() 0 -> 0.5417756875272429
2/3780 0.050 0.032 scale MinMaxScaler() 0 -> 0.5316854466803687
3/3780 0.050 0.032 auto StandardScaler() 0 -> 0.5417756875272429
4/3780 0.050 0.032 auto MinMaxScaler() 0 -> 0.6885896949658922
5/3780 0.050 0.032 0.01 StandardScaler() 0 -> 0.6350147002507263
6/3780 0.050 0.032 0.01 MinMaxScaler() 0 -> 0.7391515282840602
7/3780 0.050 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5631224105089
8/3780 0.050 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.718194108362515
9/3780 0.050 0.032 0.1 StandardScaler() 0 -> 0.5441232780771921
10/3780 0.050 0.032 0.1 MinMaxScaler() 0 -> 0.6845473818306503
11/3780 0.050 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6353615358334851
12/3780 0.050 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6224281808356801
13/3780 0.050 0.032 1.0 StandardScaler() 0 -> 0.7253388096625284
14/3780 0.050 0.032 1.0 MinMaxScaler() 0 -> 0.5486988181982922
15/3780 0.050 0.040 scale StandardScaler() 0 -> 0.5263334531021855
16/3780 0.050 0.040 scale MinMaxScaler() 0 -> 0.5196418040258937
17/3780 0.050 0.040 auto StandardScaler() 0 -> 0.5263334531021854
18/3780 0.050 0.040 auto MinMaxScaler() 0 -> 0.6787833467611174
19/3780 0.050 0.040 0.01 StandardScaler() 0 -> 0.6166508470360693
20/3780 0.050 0.040 0.01 MinMaxScaler() 0 -> 0.7347376569364087
21/3780 0.050 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5439047722218814
22/3780 0.050 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7127844895736883
23/3780 0.050 0.040 0.1 StandardScaler() 0 -> 0.5284501945375598
24/3780 0.050 0.040 0.1 MinMaxScaler() 0 -> 0.6744470358266433
25/3780 0.050 0.040 0.31622776601683794 StandardScaler() 0 -> 0.6146516921075547
26/3780 0.050 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.6015852109713965
27/3780 0.050 0.040 1.0 StandardScaler() 0 -> 0.7174509118934788
28/3780 0.050 0.040 1.0 MinMaxScaler() 0 -> 0.5326029352638648
29/3780 0.050 0.051 scale StandardScaler() 0 -> 0.5162382271808187
30/3780 0.050 0.051 scale MinMaxScaler() 0 -> 0.5120580774607112
31/3780 0.050 0.051 auto StandardScaler() 0 -> 0.5162382271808187
32/3780 0.050 0.051 auto MinMaxScaler() 0 -> 0.6668243305599088
33/3780 0.050 0.051 0.01 StandardScaler() 0 -> 0.5969668583056813
34/3780 0.050 0.051 0.01 MinMaxScaler() 0 -> 0.7302414641296567
35/3780 0.050 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5301836430561943
36/3780 0.050 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7064988571141138
37/3780 0.050 0.051 0.1 StandardScaler() 0 -> 0.5179871370063399
38/3780 0.050 0.051 0.1 MinMaxScaler() 0 -> 0.6614633230012762
39/3780 0.050 0.051 0.31622776601683794 StandardScaler() 0 -> 0.592972507735277
40/3780 0.050 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5810810904142143
41/3780 0.050 0.051 1.0 StandardScaler() 0 -> 0.7078212427052307
42/3780 0.050 0.051 1.0 MinMaxScaler() 0 -> 0.5207333864933087
43/3780 0.050 0.065 scale StandardScaler() 0 -> 0.5092032307798616
44/3780 0.050 0.065 scale MinMaxScaler() 0 -> 0.5065241217183292
45/3780 0.050 0.065 auto StandardScaler() 0 -> 0.5092032307798616
46/3780 0.050 0.065 auto MinMaxScaler() 0 -> 0.6528277491908262
47/3780 0.050 0.065 0.01 StandardScaler() 0 -> 0.5773979502622207
48/3780 0.050 0.065 0.01 MinMaxScaler() 0 -> 0.7260164027080508
49/3780 0.050 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5190697167498945
50/3780 0.050 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6994210269909642
51/3780 0.050 0.065 0.1 StandardScaler() 0 -> 0.5104755744635244
52/3780 0.050 0.065 0.1 MinMaxScaler() 0 -> 0.6467398892407229
53/3780 0.050 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5722785291129089
54/3780 0.050 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5626973752161925
55/3780 0.050 0.065 1.0 StandardScaler() 0 -> 0.696267961050013
56/3780 0.050 0.065 1.0 MinMaxScaler() 0 -> 0.5136537986189046
57/3780 0.050 0.082 scale StandardScaler() 0 -> 0.5038816496768466
58/3780 0.050 0.082 scale MinMaxScaler() 0 -> 0.50263663839903
59/3780 0.050 0.082 auto StandardScaler() 0 -> 0.5038816496768467
60/3780 0.050 0.082 auto MinMaxScaler() 0 -> 0.6365150513262353
61/3780 0.050 0.082 0.01 StandardScaler() 0 -> 0.5614692607643522
62/3780 0.050 0.082 0.01 MinMaxScaler() 0 -> 0.7220321888520793
63/3780 0.050 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5125464825253718
64/3780 0.050 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6908915698193371
65/3780 0.050 0.082 0.1 StandardScaler() 0 -> 0.5047121779024161
66/3780 0.050 0.082 0.1 MinMaxScaler() 0 -> 0.6298038621118833
67/3780 0.050 0.082 0.31622776601683794 StandardScaler() 0 -> 0.554023275520302
68/3780 0.050 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5502978965778179
69/3780 0.050 0.082 1.0 StandardScaler() 0 -> 0.6825440351963438
70/3780 0.050 0.082 1.0 MinMaxScaler() 0 -> 0.5088836689640638
71/3780 0.050 0.104 scale StandardScaler() 0 -> 0.49888679041628153
72/3780 0.050 0.104 scale MinMaxScaler() 0 -> 0.49930985082825036
73/3780 0.050 0.104 auto StandardScaler() 0 -> 0.49888679041628153
74/3780 0.050 0.104 auto MinMaxScaler() 0 -> 0.6179789583771612
75/3780 0.050 0.104 0.01 StandardScaler() 0 -> 0.5509082096431364
76/3780 0.050 0.104 0.01 MinMaxScaler() 0 -> 0.7168559986950563
77/3780 0.050 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5080716448577801
78/3780 0.050 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6814652148256535
79/3780 0.050 0.104 0.1 StandardScaler() 0 -> 0.4992027549485052
80/3780 0.050 0.104 0.1 MinMaxScaler() 0 -> 0.6102798615659029
81/3780 0.050 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5392897364138621
82/3780 0.050 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5405055127570358
83/3780 0.050 0.104 1.0 StandardScaler() 0 -> 0.666356031607992
84/3780 0.050 0.104 1.0 MinMaxScaler() 0 -> 0.5058293695158047
85/3780 0.050 0.132 scale StandardScaler() 0 -> 0.49488211134282656
86/3780 0.050 0.132 scale MinMaxScaler() 0 -> 0.49646287392214167
87/3780 0.050 0.132 auto StandardScaler() 0 -> 0.49488211134282656
88/3780 0.050 0.132 auto MinMaxScaler() 0 -> 0.5985454568721583
89/3780 0.050 0.132 0.01 StandardScaler() 0 -> 0.541368176523545
90/3780 0.050 0.132 0.01 MinMaxScaler() 0 -> 0.7114262400708505
91/3780 0.050 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5048570327170535
92/3780 0.050 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6706551848866065
93/3780 0.050 0.132 0.1 StandardScaler() 0 -> 0.49567594070777893
94/3780 0.050 0.132 0.1 MinMaxScaler() 0 -> 0.591140319534765
95/3780 0.050 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5258257942115764
96/3780 0.050 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5325298337835055
97/3780 0.050 0.132 1.0 StandardScaler() 0 -> 0.6478962649359502
98/3780 0.050 0.132 1.0 MinMaxScaler() 0 -> 0.5032112071571574
99/3780 0.050 0.168 scale StandardScaler() 0 -> 0.492295861901691
100/3780 0.050 0.168 scale MinMaxScaler() 0 -> 0.49376277847333044
101/3780 0.050 0.168 auto StandardScaler() 0 -> 0.492295861901691
102/3780 0.050 0.168 auto MinMaxScaler() 0 -> 0.5806158811946478
103/3780 0.050 0.168 0.01 StandardScaler() 0 -> 0.5327204616599012
104/3780 0.050 0.168 0.01 MinMaxScaler() 0 -> 0.7049188025073384
105/3780 0.050 0.168 0.03162277660168379 StandardScaler() 0 -> 0.502021290638413
106/3780 0.050 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6574873645649861
107/3780 0.050 0.168 0.1 StandardScaler() 0 -> 0.49241034010500423
108/3780 0.050 0.168 0.1 MinMaxScaler() 0 -> 0.573875354654806
109/3780 0.050 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5138870635576166
110/3780 0.050 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5262788926098371
111/3780 0.050 0.168 1.0 StandardScaler() 0 -> 0.6277329172592755
112/3780 0.050 0.168 1.0 MinMaxScaler() 0 -> 0.5007739804432949
113/3780 0.050 0.213 scale StandardScaler() 0 -> 0.4892660226583924
114/3780 0.050 0.213 scale MinMaxScaler() 0 -> 0.4911719670123253
115/3780 0.050 0.213 auto StandardScaler() 0 -> 0.48926602265839253
116/3780 0.050 0.213 auto MinMaxScaler() 0 -> 0.5663611807920234
117/3780 0.050 0.213 0.01 StandardScaler() 0 -> 0.5266879553950335
118/3780 0.050 0.213 0.01 MinMaxScaler() 0 -> 0.6973722061941624
119/3780 0.050 0.213 0.03162277660168379 StandardScaler() 0 -> 0.49983495565665176
120/3780 0.050 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6420673178814529
121/3780 0.050 0.213 0.1 StandardScaler() 0 -> 0.4890335277747819
122/3780 0.050 0.213 0.1 MinMaxScaler() 0 -> 0.5617929574669587
123/3780 0.050 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5029203046402447
124/3780 0.050 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5212202938973468
125/3780 0.050 0.213 1.0 StandardScaler() 0 -> 0.6060774894963301
126/3780 0.050 0.213 1.0 MinMaxScaler() 0 -> 0.4989068115346005
127/3780 0.050 0.270 scale StandardScaler() 0 -> 0.4860964115696027
128/3780 0.050 0.270 scale MinMaxScaler() 0 -> 0.48890344068106245
129/3780 0.050 0.270 auto StandardScaler() 0 -> 0.4860964115696027
130/3780 0.050 0.270 auto MinMaxScaler() 0 -> 0.5573403006377406
131/3780 0.050 0.270 0.01 StandardScaler() 0 -> 0.5213812241348851
132/3780 0.050 0.270 0.01 MinMaxScaler() 0 -> 0.6889733147160456
133/3780 0.050 0.270 0.03162277660168379 StandardScaler() 0 -> 0.4978116136655419
134/3780 0.050 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6245836362083669
135/3780 0.050 0.270 0.1 StandardScaler() 0 -> 0.4857316047525618
136/3780 0.050 0.270 0.1 MinMaxScaler() 0 -> 0.5540794087875608
137/3780 0.050 0.270 0.31622776601683794 StandardScaler() 0 -> 0.49335358402182344
138/3780 0.050 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5170533979395359
139/3780 0.050 0.270 1.0 StandardScaler() 0 -> 0.5838847005965058
140/3780 0.050 0.270 1.0 MinMaxScaler() 0 -> 0.4968198607683889
141/3780 0.050 0.342 scale StandardScaler() 0 -> 0.48385822884063856
142/3780 0.050 0.342 scale MinMaxScaler() 0 -> 0.4869433429017489
143/3780 0.050 0.342 auto StandardScaler() 0 -> 0.48385822884063856
144/3780 0.050 0.342 auto MinMaxScaler() 0 -> 0.5515557884715062
145/3780 0.050 0.342 0.01 StandardScaler() 0 -> 0.516544002379184
146/3780 0.050 0.342 0.01 MinMaxScaler() 0 -> 0.6795926604200381
147/3780 0.050 0.342 0.03162277660168379 StandardScaler() 0 -> 0.4963334429012441
148/3780 0.050 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.6049582334340049
149/3780 0.050 0.342 0.1 StandardScaler() 0 -> 0.48313689887882555
150/3780 0.050 0.342 0.1 MinMaxScaler() 0 -> 0.5489796370346286
151/3780 0.050 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4849997722637254
152/3780 0.050 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5137689696145323
153/3780 0.050 0.342 1.0 StandardScaler() 0 -> 0.5623517055705887
154/3780 0.050 0.342 1.0 MinMaxScaler() 0 -> 0.4959316658699697
155/3780 0.050 0.434 scale StandardScaler() 0 -> 0.48177610507202245
156/3780 0.050 0.434 scale MinMaxScaler() 0 -> 0.48526484728382585
157/3780 0.050 0.434 auto StandardScaler() 0 -> 0.4817761050720226
158/3780 0.050 0.434 auto MinMaxScaler() 0 -> 0.5469813430572553
159/3780 0.050 0.434 0.01 StandardScaler() 0 -> 0.512971667011457
160/3780 0.050 0.434 0.01 MinMaxScaler() 0 -> 0.6679435189832361
161/3780 0.050 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49485492292970995
162/3780 0.050 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.587109917228117
163/3780 0.050 0.434 0.1 StandardScaler() 0 -> 0.4809124922467438
164/3780 0.050 0.434 0.1 MinMaxScaler() 0 -> 0.5448684733105802
165/3780 0.050 0.434 0.31622776601683794 StandardScaler() 0 -> 0.4782819313842024
166/3780 0.050 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5102114861923459
167/3780 0.050 0.434 1.0 StandardScaler() 0 -> 0.5418592835663218
168/3780 0.050 0.434 1.0 MinMaxScaler() 0 -> 0.49458426601963873
169/3780 0.050 0.551 scale StandardScaler() 0 -> 0.4799449362490213
170/3780 0.050 0.551 scale MinMaxScaler() 0 -> 0.48374173537122384
171/3780 0.050 0.551 auto StandardScaler() 0 -> 0.47994493624902135
172/3780 0.050 0.551 auto MinMaxScaler() 0 -> 0.5431320238010807
173/3780 0.050 0.551 0.01 StandardScaler() 0 -> 0.5094728651930552
174/3780 0.050 0.551 0.01 MinMaxScaler() 0 -> 0.6545530833107155
175/3780 0.050 0.551 0.03162277660168379 StandardScaler() 0 -> 0.49369689761301633
176/3780 0.050 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5719441852266901
177/3780 0.050 0.551 0.1 StandardScaler() 0 -> 0.47933249291214786
178/3780 0.050 0.551 0.1 MinMaxScaler() 0 -> 0.5407625155705016
179/3780 0.050 0.551 0.31622776601683794 StandardScaler() 0 -> 0.47313628605332303
180/3780 0.050 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5076364355918274
181/3780 0.050 0.551 1.0 StandardScaler() 0 -> 0.5234293545723808
182/3780 0.050 0.551 1.0 MinMaxScaler() 0 -> 0.49310810644910735
183/3780 0.050 0.700 scale StandardScaler() 0 -> 0.4786954695876518
184/3780 0.050 0.700 scale MinMaxScaler() 0 -> 0.48178947340216394
185/3780 0.050 0.700 auto StandardScaler() 0 -> 0.47869546958765213
186/3780 0.050 0.700 auto MinMaxScaler() 0 -> 0.5397841965442726
187/3780 0.050 0.700 0.01 StandardScaler() 0 -> 0.5071613031173042
188/3780 0.050 0.700 0.01 MinMaxScaler() 0 -> 0.638442615188342
189/3780 0.050 0.700 0.03162277660168379 StandardScaler() 0 -> 0.4923139843359075
190/3780 0.050 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5629119247031708
191/3780 0.050 0.700 0.1 StandardScaler() 0 -> 0.47783891719753585
192/3780 0.050 0.700 0.1 MinMaxScaler() 0 -> 0.5375551447755559
193/3780 0.050 0.700 0.31622776601683794 StandardScaler() 0 -> 0.4700207967104442
194/3780 0.050 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5054551329735592
195/3780 0.050 0.700 1.0 StandardScaler() 0 -> 0.5079790435623985
196/3780 0.050 0.700 1.0 MinMaxScaler() 0 -> 0.4920508358307367
197/3780 0.050 0.888 scale StandardScaler() 0 -> 0.4778714596467147
198/3780 0.050 0.888 scale MinMaxScaler() 0 -> 0.47989753989242634
199/3780 0.050 0.888 auto StandardScaler() 0 -> 0.4778714596467144
200/3780 0.050 0.888 auto MinMaxScaler() 0 -> 0.5364895773933279
201/3780 0.050 0.888 0.01 StandardScaler() 0 -> 0.5047913278893797
202/3780 0.050 0.888 0.01 MinMaxScaler() 0 -> 0.6201396970380224
203/3780 0.050 0.888 0.03162277660168379 StandardScaler() 0 -> 0.49077376218879093
204/3780 0.050 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5576608021590969
205/3780 0.050 0.888 0.1 StandardScaler() 0 -> 0.47695470805366186
206/3780 0.050 0.888 0.1 MinMaxScaler() 0 -> 0.5335801570674343
207/3780 0.050 0.888 0.31622776601683794 StandardScaler() 0 -> 0.46912577428776414
208/3780 0.050 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5040770951262662
209/3780 0.050 0.888 1.0 StandardScaler() 0 -> 0.49589383438322177
210/3780 0.050 0.888 1.0 MinMaxScaler() 0 -> 0.4907098068890572
211/3780 0.050 1.126 scale StandardScaler() 0 -> 0.47720075255999067
212/3780 0.050 1.126 scale MinMaxScaler() 0 -> 0.47883896908678314
213/3780 0.050 1.126 auto StandardScaler() 0 -> 0.47720075255999106
214/3780 0.050 1.126 auto MinMaxScaler() 0 -> 0.5326852273930224
215/3780 0.050 1.126 0.01 StandardScaler() 0 -> 0.5029145358575807
216/3780 0.050 1.126 0.01 MinMaxScaler() 0 -> 0.6010029349504362
217/3780 0.050 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48978873346376456
218/3780 0.050 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5546354612895025
219/3780 0.050 1.126 0.1 StandardScaler() 0 -> 0.47587606221385537
220/3780 0.050 1.126 0.1 MinMaxScaler() 0 -> 0.5294591644109383
221/3780 0.050 1.126 0.31622776601683794 StandardScaler() 0 -> 0.4696320929197319
222/3780 0.050 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.502804050737248
223/3780 0.050 1.126 1.0 StandardScaler() 0 -> 0.4894757004146768
224/3780 0.050 1.126 1.0 MinMaxScaler() 0 -> 0.48897683100023115
225/3780 0.050 1.429 scale StandardScaler() 0 -> 0.47634177825847485
226/3780 0.050 1.429 scale MinMaxScaler() 0 -> 0.47778981547033944
227/3780 0.050 1.429 auto StandardScaler() 0 -> 0.47634177825847407
228/3780 0.050 1.429 auto MinMaxScaler() 0 -> 0.5288569619441066
229/3780 0.050 1.429 0.01 StandardScaler() 0 -> 0.5022616865900765
230/3780 0.050 1.429 0.01 MinMaxScaler() 0 -> 0.5842872046740216
231/3780 0.050 1.429 0.03162277660168379 StandardScaler() 0 -> 0.4890564979395216
232/3780 0.050 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5520397946219174
233/3780 0.050 1.429 0.1 StandardScaler() 0 -> 0.4755577913669315
234/3780 0.050 1.429 0.1 MinMaxScaler() 0 -> 0.5260786887078298
235/3780 0.050 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4717815460264254
236/3780 0.050 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5017900982656133
237/3780 0.050 1.429 1.0 StandardScaler() 0 -> 0.4863709684436634
238/3780 0.050 1.429 1.0 MinMaxScaler() 0 -> 0.48815063122999786
239/3780 0.050 1.814 scale StandardScaler() 0 -> 0.47646901294680616
240/3780 0.050 1.814 scale MinMaxScaler() 0 -> 0.4770957841241814
241/3780 0.050 1.814 auto StandardScaler() 0 -> 0.47646901294680527
242/3780 0.050 1.814 auto MinMaxScaler() 0 -> 0.525197630237999
243/3780 0.050 1.814 0.01 StandardScaler() 0 -> 0.5014903158340293
244/3780 0.050 1.814 0.01 MinMaxScaler() 0 -> 0.5709990287764996
245/3780 0.050 1.814 0.03162277660168379 StandardScaler() 0 -> 0.4881950704728715
246/3780 0.050 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5498530896482993
247/3780 0.050 1.814 0.1 StandardScaler() 0 -> 0.4754206218591659
248/3780 0.050 1.814 0.1 MinMaxScaler() 0 -> 0.5221301491959884
249/3780 0.050 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4752956319533748
250/3780 0.050 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.500420929565054
251/3780 0.050 1.814 1.0 StandardScaler() 0 -> 0.48492524924617136
252/3780 0.050 1.814 1.0 MinMaxScaler() 0 -> 0.4880755460672592
253/3780 0.050 2.302 scale StandardScaler() 0 -> 0.47649238229644136
254/3780 0.050 2.302 scale MinMaxScaler() 0 -> 0.4771826246825434
255/3780 0.050 2.302 auto StandardScaler() 0 -> 0.4764923822964424
256/3780 0.050 2.302 auto MinMaxScaler() 0 -> 0.5212380040120576
257/3780 0.050 2.302 0.01 StandardScaler() 0 -> 0.5006761850282923
258/3780 0.050 2.302 0.01 MinMaxScaler() 0 -> 0.5630325114017899
259/3780 0.050 2.302 0.03162277660168379 StandardScaler() 0 -> 0.4878476246134648
260/3780 0.050 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5481970078206553
261/3780 0.050 2.302 0.1 StandardScaler() 0 -> 0.4763388934483444
262/3780 0.050 2.302 0.1 MinMaxScaler() 0 -> 0.518071598481016
263/3780 0.050 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4795150945101832
264/3780 0.050 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.49943794628693383
265/3780 0.050 2.302 1.0 StandardScaler() 0 -> 0.48513299530352133
266/3780 0.050 2.302 1.0 MinMaxScaler() 0 -> 0.4876001444026205
267/3780 0.050 2.921 scale StandardScaler() 0 -> 0.478019675239727
268/3780 0.050 2.921 scale MinMaxScaler() 0 -> 0.47727206359135543
269/3780 0.050 2.921 auto StandardScaler() 0 -> 0.4780196752397275
270/3780 0.050 2.921 auto MinMaxScaler() 0 -> 0.5174477932467232
271/3780 0.050 2.921 0.01 StandardScaler() 0 -> 0.5004615422258866
272/3780 0.050 2.921 0.01 MinMaxScaler() 0 -> 0.5588793853980926
273/3780 0.050 2.921 0.03162277660168379 StandardScaler() 0 -> 0.48716314458352855
274/3780 0.050 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.545984528685402
275/3780 0.050 2.921 0.1 StandardScaler() 0 -> 0.47919464326697586
276/3780 0.050 2.921 0.1 MinMaxScaler() 0 -> 0.5146842574641702
277/3780 0.050 2.921 0.31622776601683794 StandardScaler() 0 -> 0.48459837009863
278/3780 0.050 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49871824135643666
279/3780 0.050 2.921 1.0 StandardScaler() 0 -> 0.4848980410922332
280/3780 0.050 2.921 1.0 MinMaxScaler() 0 -> 0.4866349749516988
281/3780 0.050 3.707 scale StandardScaler() 0 -> 0.4812996130000697
282/3780 0.050 3.707 scale MinMaxScaler() 0 -> 0.4782042075752319
283/3780 0.050 3.707 auto StandardScaler() 0 -> 0.48129961300007024
284/3780 0.050 3.707 auto MinMaxScaler() 0 -> 0.5139152525877925
285/3780 0.050 3.707 0.01 StandardScaler() 0 -> 0.499945962224573
286/3780 0.050 3.707 0.01 MinMaxScaler() 0 -> 0.5564037078583023
287/3780 0.050 3.707 0.03162277660168379 StandardScaler() 0 -> 0.4860680965644894
288/3780 0.050 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.543758201930447
289/3780 0.050 3.707 0.1 StandardScaler() 0 -> 0.48259161988019117
290/3780 0.050 3.707 0.1 MinMaxScaler() 0 -> 0.5116325741221334
291/3780 0.050 3.707 0.31622776601683794 StandardScaler() 0 -> 0.4925025956853694
292/3780 0.050 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4978137167373058
293/3780 0.050 3.707 1.0 StandardScaler() 0 -> 0.4848728847231576
294/3780 0.050 3.707 1.0 MinMaxScaler() 0 -> 0.48581015046631765
295/3780 0.050 4.703 scale StandardScaler() 0 -> 0.48521539374910905
296/3780 0.050 4.703 scale MinMaxScaler() 0 -> 0.4811741458787437
297/3780 0.050 4.703 auto StandardScaler() 0 -> 0.4852153937491095
298/3780 0.050 4.703 auto MinMaxScaler() 0 -> 0.5110332596787349
299/3780 0.050 4.703 0.01 StandardScaler() 0 -> 0.4992190776020074
300/3780 0.050 4.703 0.01 MinMaxScaler() 0 -> 0.5549824462117194
301/3780 0.050 4.703 0.03162277660168379 StandardScaler() 0 -> 0.4848169727475737
302/3780 0.050 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5411745934634883
303/3780 0.050 4.703 0.1 StandardScaler() 0 -> 0.4872440358128925
304/3780 0.050 4.703 0.1 MinMaxScaler() 0 -> 0.5090589684899521
305/3780 0.050 4.703 0.31622776601683794 StandardScaler() 0 -> 0.5000375543538588
306/3780 0.050 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.497232443619735
307/3780 0.050 4.703 1.0 StandardScaler() 0 -> 0.48502024181466735
308/3780 0.050 4.703 1.0 MinMaxScaler() 0 -> 0.4846776497686763
309/3780 0.050 5.968 scale StandardScaler() 0 -> 0.48999212063064346
310/3780 0.050 5.968 scale MinMaxScaler() 0 -> 0.48474594683656913
311/3780 0.050 5.968 auto StandardScaler() 0 -> 0.4899921206306464
312/3780 0.050 5.968 auto MinMaxScaler() 0 -> 0.5087776741373345
313/3780 0.050 5.968 0.01 StandardScaler() 0 -> 0.4988061011664137
314/3780 0.050 5.968 0.01 MinMaxScaler() 0 -> 0.5536405793177864
315/3780 0.050 5.968 0.03162277660168379 StandardScaler() 0 -> 0.485035790471791
316/3780 0.050 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5383253081512622
317/3780 0.050 5.968 0.1 StandardScaler() 0 -> 0.4932271983268965
318/3780 0.050 5.968 0.1 MinMaxScaler() 0 -> 0.5074415997945749
319/3780 0.050 5.968 0.31622776601683794 StandardScaler() 0 -> 0.507631838193443
320/3780 0.050 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.49709945125912536
321/3780 0.050 5.968 1.0 StandardScaler() 0 -> 0.48520301448439307
322/3780 0.050 5.968 1.0 MinMaxScaler() 0 -> 0.4842614879143099
323/3780 0.050 7.574 scale StandardScaler() 0 -> 0.4961081060922649
324/3780 0.050 7.574 scale MinMaxScaler() 0 -> 0.48905062250807685
325/3780 0.050 7.574 auto StandardScaler() 0 -> 0.49610810609225925
326/3780 0.050 7.574 auto MinMaxScaler() 0 -> 0.5068539780514866
327/3780 0.050 7.574 0.01 StandardScaler() 0 -> 0.49808096903472293
328/3780 0.050 7.574 0.01 MinMaxScaler() 0 -> 0.5526043348302329
329/3780 0.050 7.574 0.03162277660168379 StandardScaler() 0 -> 0.48534888838283247
330/3780 0.050 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5352865429219814
331/3780 0.050 7.574 0.1 StandardScaler() 0 -> 0.5011344679263556
332/3780 0.050 7.574 0.1 MinMaxScaler() 0 -> 0.5057645096682649
333/3780 0.050 7.574 0.31622776601683794 StandardScaler() 0 -> 0.517289487441889
334/3780 0.050 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.4963126440013414
335/3780 0.050 7.574 1.0 StandardScaler() 0 -> 0.4854246251199867
336/3780 0.050 7.574 1.0 MinMaxScaler() 0 -> 0.4841303242837353
337/3780 0.050 9.611 scale StandardScaler() 0 -> 0.5043105042809893
338/3780 0.050 9.611 scale MinMaxScaler() 0 -> 0.49353614472365775
339/3780 0.050 9.611 auto StandardScaler() 0 -> 0.5043105042809887
340/3780 0.050 9.611 auto MinMaxScaler() 0 -> 0.5057345750477822
341/3780 0.050 9.611 0.01 StandardScaler() 0 -> 0.49699156153007956
342/3780 0.050 9.611 0.01 MinMaxScaler() 0 -> 0.5516310642039585
343/3780 0.050 9.611 0.03162277660168379 StandardScaler() 0 -> 0.48520071793994957
344/3780 0.050 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5315806623797162
345/3780 0.050 9.611 0.1 StandardScaler() 0 -> 0.5100425377808996
346/3780 0.050 9.611 0.1 MinMaxScaler() 0 -> 0.5049315816389299
347/3780 0.050 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5286606464268088
348/3780 0.050 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4954178580184803
349/3780 0.050 9.611 1.0 StandardScaler() 0 -> 0.48554245751309305
350/3780 0.050 9.611 1.0 MinMaxScaler() 0 -> 0.48463820127628116
351/3780 0.050 12.196 scale StandardScaler() 0 -> 0.5135174856761849
352/3780 0.050 12.196 scale MinMaxScaler() 0 -> 0.4987570368688566
353/3780 0.050 12.196 auto StandardScaler() 0 -> 0.5135174856761815
354/3780 0.050 12.196 auto MinMaxScaler() 0 -> 0.5049317668273224
355/3780 0.050 12.196 0.01 StandardScaler() 0 -> 0.49623540368097335
356/3780 0.050 12.196 0.01 MinMaxScaler() 0 -> 0.5507951426911254
357/3780 0.050 12.196 0.03162277660168379 StandardScaler() 0 -> 0.4854994176002176
358/3780 0.050 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5281349523678761
359/3780 0.050 12.196 0.1 StandardScaler() 0 -> 0.5218846521742616
360/3780 0.050 12.196 0.1 MinMaxScaler() 0 -> 0.5039671865971967
361/3780 0.050 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5386867523312588
362/3780 0.050 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4948051168766044
363/3780 0.050 12.196 1.0 StandardScaler() 0 -> 0.48555008895269
364/3780 0.050 12.196 1.0 MinMaxScaler() 0 -> 0.48631183318258436
365/3780 0.050 15.476 scale StandardScaler() 0 -> 0.5261330657921803
366/3780 0.050 15.476 scale MinMaxScaler() 0 -> 0.5048631046516325
367/3780 0.050 15.476 auto StandardScaler() 0 -> 0.5261330657921771
368/3780 0.050 15.476 auto MinMaxScaler() 0 -> 0.5037421719367496
369/3780 0.050 15.476 0.01 StandardScaler() 0 -> 0.49581891882462537
370/3780 0.050 15.476 0.01 MinMaxScaler() 0 -> 0.5497539746560826
371/3780 0.050 15.476 0.03162277660168379 StandardScaler() 0 -> 0.48652268317906944
372/3780 0.050 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5243793403164361
373/3780 0.050 15.476 0.1 StandardScaler() 0 -> 0.5379229587999604
374/3780 0.050 15.476 0.1 MinMaxScaler() 0 -> 0.5030756900865695
375/3780 0.050 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5461154857546763
376/3780 0.050 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.4938970838352604
377/3780 0.050 15.476 1.0 StandardScaler() 0 -> 0.48555043132407333
378/3780 0.050 15.476 1.0 MinMaxScaler() 0 -> 0.48807007584676526
379/3780 0.050 19.638 scale StandardScaler() 0 -> 0.5430028304744362
380/3780 0.050 19.638 scale MinMaxScaler() 0 -> 0.5136643761834065
381/3780 0.050 19.638 auto StandardScaler() 0 -> 0.5430028304744393
382/3780 0.050 19.638 auto MinMaxScaler() 0 -> 0.5031589702683745
383/3780 0.050 19.638 0.01 StandardScaler() 0 -> 0.4953528656361381
384/3780 0.050 19.638 0.01 MinMaxScaler() 0 -> 0.5484255766307119
385/3780 0.050 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4883734468229941
386/3780 0.050 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5203000303497458
387/3780 0.050 19.638 0.1 StandardScaler() 0 -> 0.5563882628897346
388/3780 0.050 19.638 0.1 MinMaxScaler() 0 -> 0.5026752263147879
389/3780 0.050 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5521057438396655
390/3780 0.050 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.49321973393806456
391/3780 0.050 19.638 1.0 StandardScaler() 0 -> 0.48555356606842137
392/3780 0.050 19.638 1.0 MinMaxScaler() 0 -> 0.4891875397164016
393/3780 0.050 24.920 scale StandardScaler() 0 -> 0.5623300604968581
394/3780 0.050 24.920 scale MinMaxScaler() 0 -> 0.5265253262126989
395/3780 0.050 24.920 auto StandardScaler() 0 -> 0.5623300604968589
396/3780 0.050 24.920 auto MinMaxScaler() 0 -> 0.502831158840385
397/3780 0.050 24.920 0.01 StandardScaler() 0 -> 0.4948928955607215
398/3780 0.050 24.920 0.01 MinMaxScaler() 0 -> 0.546792402098771
399/3780 0.050 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4917208463329721
400/3780 0.050 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5166959429002883
401/3780 0.050 24.920 0.1 StandardScaler() 0 -> 0.5799347684544297
402/3780 0.050 24.920 0.1 MinMaxScaler() 0 -> 0.5022821885693142
403/3780 0.050 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5575686046572264
404/3780 0.050 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.49265900341348406
405/3780 0.050 24.920 1.0 StandardScaler() 0 -> 0.48555356606842137
406/3780 0.050 24.920 1.0 MinMaxScaler() 0 -> 0.4902652158480758
407/3780 0.050 31.623 scale StandardScaler() 0 -> 0.5864074035257794
408/3780 0.050 31.623 scale MinMaxScaler() 0 -> 0.5418619513510174
409/3780 0.050 31.623 auto StandardScaler() 0 -> 0.5864074035257774
410/3780 0.050 31.623 auto MinMaxScaler() 0 -> 0.5023839230174686
411/3780 0.050 31.623 0.01 StandardScaler() 0 -> 0.49419785614481654
412/3780 0.050 31.623 0.01 MinMaxScaler() 0 -> 0.5448047995593243
413/3780 0.050 31.623 0.03162277660168379 StandardScaler() 0 -> 0.49435021650512895
414/3780 0.050 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5135466672393257
415/3780 0.050 31.623 0.1 StandardScaler() 0 -> 0.6047210398039082
416/3780 0.050 31.623 0.1 MinMaxScaler() 0 -> 0.5018532975191449
417/3780 0.050 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5612507407994983
418/3780 0.050 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4919911987317445
419/3780 0.050 31.623 1.0 StandardScaler() 0 -> 0.48555356606842137
420/3780 0.050 31.623 1.0 MinMaxScaler() 0 -> 0.4936205008083075
421/3780 0.100 0.032 scale StandardScaler() 0 -> 0.5349297339273827
422/3780 0.100 0.032 scale MinMaxScaler() 0 -> 0.5262563913937041
423/3780 0.100 0.032 auto StandardScaler() 0 -> 0.5349297339273827
424/3780 0.100 0.032 auto MinMaxScaler() 0 -> 0.6660598353757482
425/3780 0.100 0.032 0.01 StandardScaler() 0 -> 0.6132069878979833
426/3780 0.100 0.032 0.01 MinMaxScaler() 0 -> 0.7359027327858939
427/3780 0.100 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5519408021085989
428/3780 0.100 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7020406755542864
429/3780 0.100 0.032 0.1 StandardScaler() 0 -> 0.5369369833026919
430/3780 0.100 0.032 0.1 MinMaxScaler() 0 -> 0.6622126832445979
431/3780 0.100 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6205685198960572
432/3780 0.100 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.6025866361443853
433/3780 0.100 0.032 1.0 StandardScaler() 0 -> 0.7241886498811819
434/3780 0.100 0.032 1.0 MinMaxScaler() 0 -> 0.5404499541682249
435/3780 0.100 0.040 scale StandardScaler() 0 -> 0.5233076967639502
436/3780 0.100 0.040 scale MinMaxScaler() 0 -> 0.5159826427475402
437/3780 0.100 0.040 auto StandardScaler() 0 -> 0.5233076967639501
438/3780 0.100 0.040 auto MinMaxScaler() 0 -> 0.6549265330545183
439/3780 0.100 0.040 0.01 StandardScaler() 0 -> 0.5969632257904878
440/3780 0.100 0.040 0.01 MinMaxScaler() 0 -> 0.7308228553659039
441/3780 0.100 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5377404414653157
442/3780 0.100 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.6941772999272882
443/3780 0.100 0.040 0.1 StandardScaler() 0 -> 0.5249178755341075
444/3780 0.100 0.040 0.1 MinMaxScaler() 0 -> 0.6505594664258831
445/3780 0.100 0.040 0.31622776601683794 StandardScaler() 0 -> 0.6006224352203234
446/3780 0.100 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5854480638205254
447/3780 0.100 0.040 1.0 StandardScaler() 0 -> 0.7160844076627182
448/3780 0.100 0.040 1.0 MinMaxScaler() 0 -> 0.5277577199328699
449/3780 0.100 0.051 scale StandardScaler() 0 -> 0.5144465104860847
450/3780 0.100 0.051 scale MinMaxScaler() 0 -> 0.5094695586819235
451/3780 0.100 0.051 auto StandardScaler() 0 -> 0.5144465104860848
452/3780 0.100 0.051 auto MinMaxScaler() 0 -> 0.6426872983263455
453/3780 0.100 0.051 0.01 StandardScaler() 0 -> 0.5816143862256232
454/3780 0.100 0.051 0.01 MinMaxScaler() 0 -> 0.7246090335414822
455/3780 0.100 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5261484647638434
456/3780 0.100 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6869884345471734
457/3780 0.100 0.051 0.1 StandardScaler() 0 -> 0.5161184040315704
458/3780 0.100 0.051 0.1 MinMaxScaler() 0 -> 0.6375835531765016
459/3780 0.100 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5809249876748871
460/3780 0.100 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5693540331556103
461/3780 0.100 0.051 1.0 StandardScaler() 0 -> 0.7062166255642518
462/3780 0.100 0.051 1.0 MinMaxScaler() 0 -> 0.5190149544401476
463/3780 0.100 0.065 scale StandardScaler() 0 -> 0.5077120101055533
464/3780 0.100 0.065 scale MinMaxScaler() 0 -> 0.5050212120671711
465/3780 0.100 0.065 auto StandardScaler() 0 -> 0.5077120101055533
466/3780 0.100 0.065 auto MinMaxScaler() 0 -> 0.6292773185874002
467/3780 0.100 0.065 0.01 StandardScaler() 0 -> 0.5674977408187999
468/3780 0.100 0.065 0.01 MinMaxScaler() 0 -> 0.7170744903147802
469/3780 0.100 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5180658376332344
470/3780 0.100 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6782696528858182
471/3780 0.100 0.065 0.1 StandardScaler() 0 -> 0.5083516505914428
472/3780 0.100 0.065 0.1 MinMaxScaler() 0 -> 0.6236977220450001
473/3780 0.100 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5627053210265194
474/3780 0.100 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5563960464327579
475/3780 0.100 0.065 1.0 StandardScaler() 0 -> 0.6944380001500292
476/3780 0.100 0.065 1.0 MinMaxScaler() 0 -> 0.5122878555413549
477/3780 0.100 0.082 scale StandardScaler() 0 -> 0.5022053774208236
478/3780 0.100 0.082 scale MinMaxScaler() 0 -> 0.5010579665215464
479/3780 0.100 0.082 auto StandardScaler() 0 -> 0.5022053774208235
480/3780 0.100 0.082 auto MinMaxScaler() 0 -> 0.6151096313831687
481/3780 0.100 0.082 0.01 StandardScaler() 0 -> 0.5568016145551912
482/3780 0.100 0.082 0.01 MinMaxScaler() 0 -> 0.7085101356578866
483/3780 0.100 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5121923616333088
484/3780 0.100 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6688292175747309
485/3780 0.100 0.082 0.1 StandardScaler() 0 -> 0.5029798677737486
486/3780 0.100 0.082 0.1 MinMaxScaler() 0 -> 0.6091594061448711
487/3780 0.100 0.082 0.31622776601683794 StandardScaler() 0 -> 0.546635654726574
488/3780 0.100 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5452984781777191
489/3780 0.100 0.082 1.0 StandardScaler() 0 -> 0.6803919863113784
490/3780 0.100 0.082 1.0 MinMaxScaler() 0 -> 0.5078356748154297
491/3780 0.100 0.104 scale StandardScaler() 0 -> 0.4978405996291296
492/3780 0.100 0.104 scale MinMaxScaler() 0 -> 0.49711467075766547
493/3780 0.100 0.104 auto StandardScaler() 0 -> 0.4978405996291295
494/3780 0.100 0.104 auto MinMaxScaler() 0 -> 0.5994491738320077
495/3780 0.100 0.104 0.01 StandardScaler() 0 -> 0.5471884600288838
496/3780 0.100 0.104 0.01 MinMaxScaler() 0 -> 0.7002818252093396
497/3780 0.100 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5072293020798618
498/3780 0.100 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6581926329347013
499/3780 0.100 0.104 0.1 StandardScaler() 0 -> 0.49840873040957767
500/3780 0.100 0.104 0.1 MinMaxScaler() 0 -> 0.5931834002202564
501/3780 0.100 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5329851125025944
502/3780 0.100 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5376707967517069
503/3780 0.100 0.104 1.0 StandardScaler() 0 -> 0.6640110978145867
504/3780 0.100 0.104 1.0 MinMaxScaler() 0 -> 0.5040615845271951
505/3780 0.100 0.132 scale StandardScaler() 0 -> 0.4943320232198333
506/3780 0.100 0.132 scale MinMaxScaler() 0 -> 0.4941342742847499
507/3780 0.100 0.132 auto StandardScaler() 0 -> 0.49433202321983316
508/3780 0.100 0.132 auto MinMaxScaler() 0 -> 0.5845021165542609
509/3780 0.100 0.132 0.01 StandardScaler() 0 -> 0.538749308143856
510/3780 0.100 0.132 0.01 MinMaxScaler() 0 -> 0.6924646796990278
511/3780 0.100 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5034569090377948
512/3780 0.100 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6464959519233989
513/3780 0.100 0.132 0.1 StandardScaler() 0 -> 0.49464696176503736
514/3780 0.100 0.132 0.1 MinMaxScaler() 0 -> 0.578707405787238
515/3780 0.100 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5206423987507397
516/3780 0.100 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5319342851768708
517/3780 0.100 0.132 1.0 StandardScaler() 0 -> 0.6457739037969696
518/3780 0.100 0.132 1.0 MinMaxScaler() 0 -> 0.5017042957148247
519/3780 0.100 0.168 scale StandardScaler() 0 -> 0.4914648170417797
520/3780 0.100 0.168 scale MinMaxScaler() 0 -> 0.49183486532594506
521/3780 0.100 0.168 auto StandardScaler() 0 -> 0.4914648170417797
522/3780 0.100 0.168 auto MinMaxScaler() 0 -> 0.5714835617871309
523/3780 0.100 0.168 0.01 StandardScaler() 0 -> 0.5322055700790664
524/3780 0.100 0.168 0.01 MinMaxScaler() 0 -> 0.6852014808263333
525/3780 0.100 0.168 0.03162277660168379 StandardScaler() 0 -> 0.500592432376298
526/3780 0.100 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6335137902516008
527/3780 0.100 0.168 0.1 StandardScaler() 0 -> 0.49100516286477386
528/3780 0.100 0.168 0.1 MinMaxScaler() 0 -> 0.5668651336709538
529/3780 0.100 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5094888456564314
530/3780 0.100 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.526719341403465
531/3780 0.100 0.168 1.0 StandardScaler() 0 -> 0.6260569999320288
532/3780 0.100 0.168 1.0 MinMaxScaler() 0 -> 0.49914458142673174
533/3780 0.100 0.213 scale StandardScaler() 0 -> 0.48834902680099884
534/3780 0.100 0.213 scale MinMaxScaler() 0 -> 0.4891552983084448
535/3780 0.100 0.213 auto StandardScaler() 0 -> 0.48834902680099884
536/3780 0.100 0.213 auto MinMaxScaler() 0 -> 0.5617232554602616
537/3780 0.100 0.213 0.01 StandardScaler() 0 -> 0.526700197184956
538/3780 0.100 0.213 0.01 MinMaxScaler() 0 -> 0.6761436161460398
539/3780 0.100 0.213 0.03162277660168379 StandardScaler() 0 -> 0.49760372334880865
540/3780 0.100 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6199268911407706
541/3780 0.100 0.213 0.1 StandardScaler() 0 -> 0.48794263189065473
542/3780 0.100 0.213 0.1 MinMaxScaler() 0 -> 0.5585708939538419
543/3780 0.100 0.213 0.31622776601683794 StandardScaler() 0 -> 0.49940216337412274
544/3780 0.100 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5220010927285198
545/3780 0.100 0.213 1.0 StandardScaler() 0 -> 0.6050947635060709
546/3780 0.100 0.213 1.0 MinMaxScaler() 0 -> 0.49713702873348375
547/3780 0.100 0.270 scale StandardScaler() 0 -> 0.48527957229295615
548/3780 0.100 0.270 scale MinMaxScaler() 0 -> 0.48692063139607633
549/3780 0.100 0.270 auto StandardScaler() 0 -> 0.4852795722929561
550/3780 0.100 0.270 auto MinMaxScaler() 0 -> 0.5551341926043883
551/3780 0.100 0.270 0.01 StandardScaler() 0 -> 0.5222522658346923
552/3780 0.100 0.270 0.01 MinMaxScaler() 0 -> 0.6666783106324731
553/3780 0.100 0.270 0.03162277660168379 StandardScaler() 0 -> 0.49544519548758603
554/3780 0.100 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.6052223619017029
555/3780 0.100 0.270 0.1 StandardScaler() 0 -> 0.4846905799780028
556/3780 0.100 0.270 0.1 MinMaxScaler() 0 -> 0.5525146614124165
557/3780 0.100 0.270 0.31622776601683794 StandardScaler() 0 -> 0.4902171982926434
558/3780 0.100 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5181558010610424
559/3780 0.100 0.270 1.0 StandardScaler() 0 -> 0.583907753497848
560/3780 0.100 0.270 1.0 MinMaxScaler() 0 -> 0.49559664552386457
561/3780 0.100 0.342 scale StandardScaler() 0 -> 0.48253316483548486
562/3780 0.100 0.342 scale MinMaxScaler() 0 -> 0.48520204168433095
563/3780 0.100 0.342 auto StandardScaler() 0 -> 0.482533164835485
564/3780 0.100 0.342 auto MinMaxScaler() 0 -> 0.5504087070523677
565/3780 0.100 0.342 0.01 StandardScaler() 0 -> 0.5180478393146118
566/3780 0.100 0.342 0.01 MinMaxScaler() 0 -> 0.655782429136944
567/3780 0.100 0.342 0.03162277660168379 StandardScaler() 0 -> 0.49441496715330185
568/3780 0.100 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5904606277616443
569/3780 0.100 0.342 0.1 StandardScaler() 0 -> 0.4817730056758737
570/3780 0.100 0.342 0.1 MinMaxScaler() 0 -> 0.547857034961284
571/3780 0.100 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4822026811815756
572/3780 0.100 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.513984576132152
573/3780 0.100 0.342 1.0 StandardScaler() 0 -> 0.5631874581603736
574/3780 0.100 0.342 1.0 MinMaxScaler() 0 -> 0.4942353764049117
575/3780 0.100 0.434 scale StandardScaler() 0 -> 0.48024172748964716
576/3780 0.100 0.434 scale MinMaxScaler() 0 -> 0.48318604338037535
577/3780 0.100 0.434 auto StandardScaler() 0 -> 0.4802417274896474
578/3780 0.100 0.434 auto MinMaxScaler() 0 -> 0.5465463857757088
579/3780 0.100 0.434 0.01 StandardScaler() 0 -> 0.5136520545966908
580/3780 0.100 0.434 0.01 MinMaxScaler() 0 -> 0.6436874163882988
581/3780 0.100 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49349603277111304
582/3780 0.100 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5769889164314436
583/3780 0.100 0.434 0.1 StandardScaler() 0 -> 0.4798316136136331
584/3780 0.100 0.434 0.1 MinMaxScaler() 0 -> 0.544385686689866
585/3780 0.100 0.434 0.31622776601683794 StandardScaler() 0 -> 0.47598196698358936
586/3780 0.100 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5103168048835748
587/3780 0.100 0.434 1.0 StandardScaler() 0 -> 0.543199736836456
588/3780 0.100 0.434 1.0 MinMaxScaler() 0 -> 0.4933212131545981
589/3780 0.100 0.551 scale StandardScaler() 0 -> 0.47871878652773886
590/3780 0.100 0.551 scale MinMaxScaler() 0 -> 0.4811501562413611
591/3780 0.100 0.551 auto StandardScaler() 0 -> 0.4787187865277389
592/3780 0.100 0.551 auto MinMaxScaler() 0 -> 0.5436914732906393
593/3780 0.100 0.551 0.01 StandardScaler() 0 -> 0.5098179011572286
594/3780 0.100 0.551 0.01 MinMaxScaler() 0 -> 0.6306941009102683
595/3780 0.100 0.551 0.03162277660168379 StandardScaler() 0 -> 0.49191384815910116
596/3780 0.100 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5670950149143068
597/3780 0.100 0.551 0.1 StandardScaler() 0 -> 0.4783273084450048
598/3780 0.100 0.551 0.1 MinMaxScaler() 0 -> 0.5412776159452145
599/3780 0.100 0.551 0.31622776601683794 StandardScaler() 0 -> 0.47112597644158877
600/3780 0.100 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5067348303349396
601/3780 0.100 0.551 1.0 StandardScaler() 0 -> 0.52516308299533
602/3780 0.100 0.551 1.0 MinMaxScaler() 0 -> 0.4922295167971315
603/3780 0.100 0.700 scale StandardScaler() 0 -> 0.4776316419731807
604/3780 0.100 0.700 scale MinMaxScaler() 0 -> 0.4793893706410925
605/3780 0.100 0.700 auto StandardScaler() 0 -> 0.47763164197318075
606/3780 0.100 0.700 auto MinMaxScaler() 0 -> 0.5400765101514361
607/3780 0.100 0.700 0.01 StandardScaler() 0 -> 0.5064291620983427
608/3780 0.100 0.700 0.01 MinMaxScaler() 0 -> 0.6171881465744146
609/3780 0.100 0.700 0.03162277660168379 StandardScaler() 0 -> 0.49025833797675955
610/3780 0.100 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5604085806164975
611/3780 0.100 0.700 0.1 StandardScaler() 0 -> 0.4768459071837609
612/3780 0.100 0.700 0.1 MinMaxScaler() 0 -> 0.5377086612484944
613/3780 0.100 0.700 0.31622776601683794 StandardScaler() 0 -> 0.46806763221647474
614/3780 0.100 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5046029101680065
615/3780 0.100 0.700 1.0 StandardScaler() 0 -> 0.509587688063752
616/3780 0.100 0.700 1.0 MinMaxScaler() 0 -> 0.49022234896485584
617/3780 0.100 0.888 scale StandardScaler() 0 -> 0.4766635921162978
618/3780 0.100 0.888 scale MinMaxScaler() 0 -> 0.4779284171846258
619/3780 0.100 0.888 auto StandardScaler() 0 -> 0.47666359211629716
620/3780 0.100 0.888 auto MinMaxScaler() 0 -> 0.5366281259604778
621/3780 0.100 0.888 0.01 StandardScaler() 0 -> 0.5042764059177678
622/3780 0.100 0.888 0.01 MinMaxScaler() 0 -> 0.6022538954111104
623/3780 0.100 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4884560506597638
624/3780 0.100 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5567707660548521
625/3780 0.100 0.888 0.1 StandardScaler() 0 -> 0.47533318389259466
626/3780 0.100 0.888 0.1 MinMaxScaler() 0 -> 0.5339294435448553
627/3780 0.100 0.888 0.31622776601683794 StandardScaler() 0 -> 0.46684387796223986
628/3780 0.100 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5026373053223053
629/3780 0.100 0.888 1.0 StandardScaler() 0 -> 0.4972504647634007
630/3780 0.100 0.888 1.0 MinMaxScaler() 0 -> 0.4883036265273635
631/3780 0.100 1.126 scale StandardScaler() 0 -> 0.4753341310761581
632/3780 0.100 1.126 scale MinMaxScaler() 0 -> 0.47682662822581395
633/3780 0.100 1.126 auto StandardScaler() 0 -> 0.4753341310761585
634/3780 0.100 1.126 auto MinMaxScaler() 0 -> 0.5329387375252127
635/3780 0.100 1.126 0.01 StandardScaler() 0 -> 0.5022739058077571
636/3780 0.100 1.126 0.01 MinMaxScaler() 0 -> 0.5878722443102125
637/3780 0.100 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48742352021058544
638/3780 0.100 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5540878782650774
639/3780 0.100 1.126 0.1 StandardScaler() 0 -> 0.47424179822315987
640/3780 0.100 1.126 0.1 MinMaxScaler() 0 -> 0.530142287513462
641/3780 0.100 1.126 0.31622776601683794 StandardScaler() 0 -> 0.46682448264015813
642/3780 0.100 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5011237421171298
643/3780 0.100 1.126 1.0 StandardScaler() 0 -> 0.4909845304340323
644/3780 0.100 1.126 1.0 MinMaxScaler() 0 -> 0.48692022049607914
645/3780 0.100 1.429 scale StandardScaler() 0 -> 0.474140838818006
646/3780 0.100 1.429 scale MinMaxScaler() 0 -> 0.476455376780053
647/3780 0.100 1.429 auto StandardScaler() 0 -> 0.4741408388180057
648/3780 0.100 1.429 auto MinMaxScaler() 0 -> 0.5293983160929647
649/3780 0.100 1.429 0.01 StandardScaler() 0 -> 0.5013891730794916
650/3780 0.100 1.429 0.01 MinMaxScaler() 0 -> 0.5756743560809251
651/3780 0.100 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48655880121022516
652/3780 0.100 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.551706012164311
653/3780 0.100 1.429 0.1 StandardScaler() 0 -> 0.47320797799152053
654/3780 0.100 1.429 0.1 MinMaxScaler() 0 -> 0.5266215701015984
655/3780 0.100 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4686404746574397
656/3780 0.100 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.500042505577304
657/3780 0.100 1.429 1.0 StandardScaler() 0 -> 0.4876998912264772
658/3780 0.100 1.429 1.0 MinMaxScaler() 0 -> 0.48576336219884547
659/3780 0.100 1.814 scale StandardScaler() 0 -> 0.4735715102143718
660/3780 0.100 1.814 scale MinMaxScaler() 0 -> 0.4760446022151886
661/3780 0.100 1.814 auto StandardScaler() 0 -> 0.4735715102143714
662/3780 0.100 1.814 auto MinMaxScaler() 0 -> 0.5257758856999645
663/3780 0.100 1.814 0.01 StandardScaler() 0 -> 0.5004094065374772
664/3780 0.100 1.814 0.01 MinMaxScaler() 0 -> 0.5665720180217542
665/3780 0.100 1.814 0.03162277660168379 StandardScaler() 0 -> 0.48586145647933004
666/3780 0.100 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.550056321913005
667/3780 0.100 1.814 0.1 StandardScaler() 0 -> 0.47358875587706256
668/3780 0.100 1.814 0.1 MinMaxScaler() 0 -> 0.5229067969353434
669/3780 0.100 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4714890929383917
670/3780 0.100 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.49880158026465543
671/3780 0.100 1.814 1.0 StandardScaler() 0 -> 0.4860428184849399
672/3780 0.100 1.814 1.0 MinMaxScaler() 0 -> 0.4849527238050539
673/3780 0.100 2.302 scale StandardScaler() 0 -> 0.4740991497145077
674/3780 0.100 2.302 scale MinMaxScaler() 0 -> 0.4754414134511107
675/3780 0.100 2.302 auto StandardScaler() 0 -> 0.47409914971450884
676/3780 0.100 2.302 auto MinMaxScaler() 0 -> 0.5218489696413288
677/3780 0.100 2.302 0.01 StandardScaler() 0 -> 0.4993131619602491
678/3780 0.100 2.302 0.01 MinMaxScaler() 0 -> 0.5615232927574111
679/3780 0.100 2.302 0.03162277660168379 StandardScaler() 0 -> 0.4845131745613147
680/3780 0.100 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5479180805465952
681/3780 0.100 2.302 0.1 StandardScaler() 0 -> 0.47374654036595515
682/3780 0.100 2.302 0.1 MinMaxScaler() 0 -> 0.5189625414989957
683/3780 0.100 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4749156615517629
684/3780 0.100 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.4984867318898621
685/3780 0.100 2.302 1.0 StandardScaler() 0 -> 0.4860640980027749
686/3780 0.100 2.302 1.0 MinMaxScaler() 0 -> 0.48386679369041347
687/3780 0.100 2.921 scale StandardScaler() 0 -> 0.47478960675602533
688/3780 0.100 2.921 scale MinMaxScaler() 0 -> 0.4751050965130265
689/3780 0.100 2.921 auto StandardScaler() 0 -> 0.4747896067560255
690/3780 0.100 2.921 auto MinMaxScaler() 0 -> 0.5179070444208849
691/3780 0.100 2.921 0.01 StandardScaler() 0 -> 0.498941829681048
692/3780 0.100 2.921 0.01 MinMaxScaler() 0 -> 0.5584837982340841
693/3780 0.100 2.921 0.03162277660168379 StandardScaler() 0 -> 0.4834535371740951
694/3780 0.100 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5458997716163552
695/3780 0.100 2.921 0.1 StandardScaler() 0 -> 0.4754859015629605
696/3780 0.100 2.921 0.1 MinMaxScaler() 0 -> 0.5150612486980345
697/3780 0.100 2.921 0.31622776601683794 StandardScaler() 0 -> 0.47991533111721013
698/3780 0.100 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.497949827486277
699/3780 0.100 2.921 1.0 StandardScaler() 0 -> 0.48585123951999987
700/3780 0.100 2.921 1.0 MinMaxScaler() 0 -> 0.4829816144167414
701/3780 0.100 3.707 scale StandardScaler() 0 -> 0.4774081482432833
702/3780 0.100 3.707 scale MinMaxScaler() 0 -> 0.47518268257138546
703/3780 0.100 3.707 auto StandardScaler() 0 -> 0.4774081482432833
704/3780 0.100 3.707 auto MinMaxScaler() 0 -> 0.5141707376495898
705/3780 0.100 3.707 0.01 StandardScaler() 0 -> 0.4991888081124061
706/3780 0.100 3.707 0.01 MinMaxScaler() 0 -> 0.5563655235660211
707/3780 0.100 3.707 0.03162277660168379 StandardScaler() 0 -> 0.48238871734250277
708/3780 0.100 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5435973061381422
709/3780 0.100 3.707 0.1 StandardScaler() 0 -> 0.4785370607212862
710/3780 0.100 3.707 0.1 MinMaxScaler() 0 -> 0.5116373264436402
711/3780 0.100 3.707 0.31622776601683794 StandardScaler() 0 -> 0.48694333422397335
712/3780 0.100 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4969930011008896
713/3780 0.100 3.707 1.0 StandardScaler() 0 -> 0.48587013400294693
714/3780 0.100 3.707 1.0 MinMaxScaler() 0 -> 0.48215416417398577
715/3780 0.100 4.703 scale StandardScaler() 0 -> 0.48113393042519875
716/3780 0.100 4.703 scale MinMaxScaler() 0 -> 0.47750152112006705
717/3780 0.100 4.703 auto StandardScaler() 0 -> 0.48113393042520053
718/3780 0.100 4.703 auto MinMaxScaler() 0 -> 0.5112443379174744
719/3780 0.100 4.703 0.01 StandardScaler() 0 -> 0.4987222391378278
720/3780 0.100 4.703 0.01 MinMaxScaler() 0 -> 0.5547282881840082
721/3780 0.100 4.703 0.03162277660168379 StandardScaler() 0 -> 0.4814794029962434
722/3780 0.100 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5409208513823048
723/3780 0.100 4.703 0.1 StandardScaler() 0 -> 0.4816630589457039
724/3780 0.100 4.703 0.1 MinMaxScaler() 0 -> 0.5086920388525754
725/3780 0.100 4.703 0.31622776601683794 StandardScaler() 0 -> 0.4929105066865396
726/3780 0.100 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.49623293045575667
727/3780 0.100 4.703 1.0 StandardScaler() 0 -> 0.48599601034359946
728/3780 0.100 4.703 1.0 MinMaxScaler() 0 -> 0.4821028452363245
729/3780 0.100 5.968 scale StandardScaler() 0 -> 0.48441355133324243
730/3780 0.100 5.968 scale MinMaxScaler() 0 -> 0.4813560346701187
731/3780 0.100 5.968 auto StandardScaler() 0 -> 0.48441355133324443
732/3780 0.100 5.968 auto MinMaxScaler() 0 -> 0.5082070577727078
733/3780 0.100 5.968 0.01 StandardScaler() 0 -> 0.49767995213872435
734/3780 0.100 5.968 0.01 MinMaxScaler() 0 -> 0.5537437816473146
735/3780 0.100 5.968 0.03162277660168379 StandardScaler() 0 -> 0.4811087255393076
736/3780 0.100 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5384740953515833
737/3780 0.100 5.968 0.1 StandardScaler() 0 -> 0.48758736714941514
738/3780 0.100 5.968 0.1 MinMaxScaler() 0 -> 0.506462686487268
739/3780 0.100 5.968 0.31622776601683794 StandardScaler() 0 -> 0.4996965724099797
740/3780 0.100 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.4954402411450727
741/3780 0.100 5.968 1.0 StandardScaler() 0 -> 0.48618975945820503
742/3780 0.100 5.968 1.0 MinMaxScaler() 0 -> 0.4820360878239665
743/3780 0.100 7.574 scale StandardScaler() 0 -> 0.49032932166254
744/3780 0.100 7.574 scale MinMaxScaler() 0 -> 0.4856438567814352
745/3780 0.100 7.574 auto StandardScaler() 0 -> 0.490329321662537
746/3780 0.100 7.574 auto MinMaxScaler() 0 -> 0.5060879564716095
747/3780 0.100 7.574 0.01 StandardScaler() 0 -> 0.4967569778323988
748/3780 0.100 7.574 0.01 MinMaxScaler() 0 -> 0.552908146658191
749/3780 0.100 7.574 0.03162277660168379 StandardScaler() 0 -> 0.4811215039469477
750/3780 0.100 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5352727731278936
751/3780 0.100 7.574 0.1 StandardScaler() 0 -> 0.4945246566248529
752/3780 0.100 7.574 0.1 MinMaxScaler() 0 -> 0.5046583390718432
753/3780 0.100 7.574 0.31622776601683794 StandardScaler() 0 -> 0.5090664776655826
754/3780 0.100 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.4948929842417297
755/3780 0.100 7.574 1.0 StandardScaler() 0 -> 0.486382063915811
756/3780 0.100 7.574 1.0 MinMaxScaler() 0 -> 0.48202949715013793
757/3780 0.100 9.611 scale StandardScaler() 0 -> 0.4976141014678224
758/3780 0.100 9.611 scale MinMaxScaler() 0 -> 0.4893741618526464
759/3780 0.100 9.611 auto StandardScaler() 0 -> 0.49761410146782276
760/3780 0.100 9.611 auto MinMaxScaler() 0 -> 0.5044074422153472
761/3780 0.100 9.611 0.01 StandardScaler() 0 -> 0.4958807798773368
762/3780 0.100 9.611 0.01 MinMaxScaler() 0 -> 0.5517139627668771
763/3780 0.100 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4814395251716823
764/3780 0.100 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5317785912262327
765/3780 0.100 9.611 0.1 StandardScaler() 0 -> 0.5030871740150807
766/3780 0.100 9.611 0.1 MinMaxScaler() 0 -> 0.5031791514910157
767/3780 0.100 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5186372536254732
768/3780 0.100 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4939659442707207
769/3780 0.100 9.611 1.0 StandardScaler() 0 -> 0.48639348390068604
770/3780 0.100 9.611 1.0 MinMaxScaler() 0 -> 0.4827016185555057
771/3780 0.100 12.196 scale StandardScaler() 0 -> 0.507094241506994
772/3780 0.100 12.196 scale MinMaxScaler() 0 -> 0.4934777209461369
773/3780 0.100 12.196 auto StandardScaler() 0 -> 0.507094241506997
774/3780 0.100 12.196 auto MinMaxScaler() 0 -> 0.502780248117338
775/3780 0.100 12.196 0.01 StandardScaler() 0 -> 0.4952054346317505
776/3780 0.100 12.196 0.01 MinMaxScaler() 0 -> 0.5507495987446004
777/3780 0.100 12.196 0.03162277660168379 StandardScaler() 0 -> 0.48251123723099915
778/3780 0.100 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5279353337767563
779/3780 0.100 12.196 0.1 StandardScaler() 0 -> 0.5148181565096288
780/3780 0.100 12.196 0.1 MinMaxScaler() 0 -> 0.5020147127129305
781/3780 0.100 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5269212876897509
782/3780 0.100 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.49326527962177646
783/3780 0.100 12.196 1.0 StandardScaler() 0 -> 0.48640667773675617
784/3780 0.100 12.196 1.0 MinMaxScaler() 0 -> 0.4835296716274608
785/3780 0.100 15.476 scale StandardScaler() 0 -> 0.5191504846445183
786/3780 0.100 15.476 scale MinMaxScaler() 0 -> 0.4988715665057384
787/3780 0.100 15.476 auto StandardScaler() 0 -> 0.5191504846445115
788/3780 0.100 15.476 auto MinMaxScaler() 0 -> 0.501879482891696
789/3780 0.100 15.476 0.01 StandardScaler() 0 -> 0.49450868688708605
790/3780 0.100 15.476 0.01 MinMaxScaler() 0 -> 0.5496835857481418
791/3780 0.100 15.476 0.03162277660168379 StandardScaler() 0 -> 0.4829453725395188
792/3780 0.100 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5245679606055834
793/3780 0.100 15.476 0.1 StandardScaler() 0 -> 0.5304382227984008
794/3780 0.100 15.476 0.1 MinMaxScaler() 0 -> 0.501227369010865
795/3780 0.100 15.476 0.31622776601683794 StandardScaler() 0 -> 0.532191145403773
796/3780 0.100 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.49336238608284605
797/3780 0.100 15.476 1.0 StandardScaler() 0 -> 0.48640849582906814
798/3780 0.100 15.476 1.0 MinMaxScaler() 0 -> 0.48402412588192467
799/3780 0.100 19.638 scale StandardScaler() 0 -> 0.5355234362615252
800/3780 0.100 19.638 scale MinMaxScaler() 0 -> 0.5081661672837512
801/3780 0.100 19.638 auto StandardScaler() 0 -> 0.5355234362615223
802/3780 0.100 19.638 auto MinMaxScaler() 0 -> 0.5013483654159947
803/3780 0.100 19.638 0.01 StandardScaler() 0 -> 0.49337362950196056
804/3780 0.100 19.638 0.01 MinMaxScaler() 0 -> 0.5484108477674613
805/3780 0.100 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4842699810612829
806/3780 0.100 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5209833155670308
807/3780 0.100 19.638 0.1 StandardScaler() 0 -> 0.5482628416103601
808/3780 0.100 19.638 0.1 MinMaxScaler() 0 -> 0.5014754467211406
809/3780 0.100 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5366379205210722
810/3780 0.100 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.4930358911179343
811/3780 0.100 19.638 1.0 StandardScaler() 0 -> 0.48640849582906814
812/3780 0.100 19.638 1.0 MinMaxScaler() 0 -> 0.4851013816243847
813/3780 0.100 24.920 scale StandardScaler() 0 -> 0.5537228722153048
814/3780 0.100 24.920 scale MinMaxScaler() 0 -> 0.5194257383448208
815/3780 0.100 24.920 auto StandardScaler() 0 -> 0.5537228722153085
816/3780 0.100 24.920 auto MinMaxScaler() 0 -> 0.5014693229433919
817/3780 0.100 24.920 0.01 StandardScaler() 0 -> 0.4924018531356644
818/3780 0.100 24.920 0.01 MinMaxScaler() 0 -> 0.5466204853453185
819/3780 0.100 24.920 0.03162277660168379 StandardScaler() 0 -> 0.48768829010304265
820/3780 0.100 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5172824012904434
821/3780 0.100 24.920 0.1 StandardScaler() 0 -> 0.5698509777587301
822/3780 0.100 24.920 0.1 MinMaxScaler() 0 -> 0.5004267625760654
823/3780 0.100 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5410570633122722
824/3780 0.100 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.4919641555338174
825/3780 0.100 24.920 1.0 StandardScaler() 0 -> 0.48640849582906814
826/3780 0.100 24.920 1.0 MinMaxScaler() 0 -> 0.4870447082334668
827/3780 0.100 31.623 scale StandardScaler() 0 -> 0.5769057691215922
828/3780 0.100 31.623 scale MinMaxScaler() 0 -> 0.5338176174757588
829/3780 0.100 31.623 auto StandardScaler() 0 -> 0.576905769121595
830/3780 0.100 31.623 auto MinMaxScaler() 0 -> 0.5004178235020801
831/3780 0.100 31.623 0.01 StandardScaler() 0 -> 0.49234051587592503
832/3780 0.100 31.623 0.01 MinMaxScaler() 0 -> 0.5444945733520847
833/3780 0.100 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4904274246947377
834/3780 0.100 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.51367069211362
835/3780 0.100 31.623 0.1 StandardScaler() 0 -> 0.5944468382847211
836/3780 0.100 31.623 0.1 MinMaxScaler() 0 -> 0.5000592886978467
837/3780 0.100 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5438794120479101
838/3780 0.100 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.49075124733940284
839/3780 0.100 31.623 1.0 StandardScaler() 0 -> 0.48640849582906814
840/3780 0.100 31.623 1.0 MinMaxScaler() 0 -> 0.4902619518613041
841/3780 0.150 0.032 scale StandardScaler() 0 -> 0.53082299269767
842/3780 0.150 0.032 scale MinMaxScaler() 0 -> 0.5229781187063733
843/3780 0.150 0.032 auto StandardScaler() 0 -> 0.5308229926976699
844/3780 0.150 0.032 auto MinMaxScaler() 0 -> 0.6504138507006866
845/3780 0.150 0.032 0.01 StandardScaler() 0 -> 0.5981653136246633
846/3780 0.150 0.032 0.01 MinMaxScaler() 0 -> 0.7376539372877273
847/3780 0.150 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5449296642356711
848/3780 0.150 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.6977569042045325
849/3780 0.150 0.032 0.1 StandardScaler() 0 -> 0.5326126913540069
850/3780 0.150 0.032 0.1 MinMaxScaler() 0 -> 0.6458954620942747
851/3780 0.150 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6106945522240904
852/3780 0.150 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5866708480437643
853/3780 0.150 0.032 1.0 StandardScaler() 0 -> 0.728257548010982
854/3780 0.150 0.032 1.0 MinMaxScaler() 0 -> 0.5346752115132645
855/3780 0.150 0.040 scale StandardScaler() 0 -> 0.5204251815386379
856/3780 0.150 0.040 scale MinMaxScaler() 0 -> 0.5150684308437418
857/3780 0.150 0.040 auto StandardScaler() 0 -> 0.5204251815386379
858/3780 0.150 0.040 auto MinMaxScaler() 0 -> 0.6384872560996077
859/3780 0.150 0.040 0.01 StandardScaler() 0 -> 0.5831388000206928
860/3780 0.150 0.040 0.01 MinMaxScaler() 0 -> 0.7320256625129898
861/3780 0.150 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5327582561332195
862/3780 0.150 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.6852516296689038
863/3780 0.150 0.040 0.1 StandardScaler() 0 -> 0.5220434839836581
864/3780 0.150 0.040 0.1 MinMaxScaler() 0 -> 0.6340820605259161
865/3780 0.150 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5922695978105973
866/3780 0.150 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5723463333487945
867/3780 0.150 0.040 1.0 StandardScaler() 0 -> 0.7202257999492646
868/3780 0.150 0.040 1.0 MinMaxScaler() 0 -> 0.5248049487947042
869/3780 0.150 0.051 scale StandardScaler() 0 -> 0.5127795631944375
870/3780 0.150 0.051 scale MinMaxScaler() 0 -> 0.5093033675485857
871/3780 0.150 0.051 auto StandardScaler() 0 -> 0.5127795631944374
872/3780 0.150 0.051 auto MinMaxScaler() 0 -> 0.6260736169644816
873/3780 0.150 0.051 0.01 StandardScaler() 0 -> 0.5709741855354418
874/3780 0.150 0.051 0.01 MinMaxScaler() 0 -> 0.7251159458311548
875/3780 0.150 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5241611202736048
876/3780 0.150 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6738658825489194
877/3780 0.150 0.051 0.1 StandardScaler() 0 -> 0.5138655264534542
878/3780 0.150 0.051 0.1 MinMaxScaler() 0 -> 0.6211829408357238
879/3780 0.150 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5735817686387931
880/3780 0.150 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5600695166972165
881/3780 0.150 0.051 1.0 StandardScaler() 0 -> 0.710345680259799
882/3780 0.150 0.051 1.0 MinMaxScaler() 0 -> 0.518256106018962
883/3780 0.150 0.065 scale StandardScaler() 0 -> 0.50674868035008
884/3780 0.150 0.065 scale MinMaxScaler() 0 -> 0.5045532274916998
885/3780 0.150 0.065 auto StandardScaler() 0 -> 0.50674868035008
886/3780 0.150 0.065 auto MinMaxScaler() 0 -> 0.612489435610696
887/3780 0.150 0.065 0.01 StandardScaler() 0 -> 0.5610521008234514
888/3780 0.150 0.065 0.01 MinMaxScaler() 0 -> 0.716703349061734
889/3780 0.150 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5170361383755951
890/3780 0.150 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6632488334190637
891/3780 0.150 0.065 0.1 StandardScaler() 0 -> 0.5076125970564213
892/3780 0.150 0.065 0.1 MinMaxScaler() 0 -> 0.6072357589495293
893/3780 0.150 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5566420582157264
894/3780 0.150 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.550512384093604
895/3780 0.150 0.065 1.0 StandardScaler() 0 -> 0.6983342106251825
896/3780 0.150 0.065 1.0 MinMaxScaler() 0 -> 0.5133479339857577
897/3780 0.150 0.082 scale StandardScaler() 0 -> 0.5012307612083019
898/3780 0.150 0.082 scale MinMaxScaler() 0 -> 0.5002157483011253
899/3780 0.150 0.082 auto StandardScaler() 0 -> 0.5012307612083019
900/3780 0.150 0.082 auto MinMaxScaler() 0 -> 0.5982571220354198
901/3780 0.150 0.082 0.01 StandardScaler() 0 -> 0.551789057593292
902/3780 0.150 0.082 0.01 MinMaxScaler() 0 -> 0.7066512598257102
903/3780 0.150 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5118331830614492
904/3780 0.150 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6535764067582349
905/3780 0.150 0.082 0.1 StandardScaler() 0 -> 0.5019195144848271
906/3780 0.150 0.082 0.1 MinMaxScaler() 0 -> 0.5926559732789568
907/3780 0.150 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5428057769334469
908/3780 0.150 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5429392461789486
909/3780 0.150 0.082 1.0 StandardScaler() 0 -> 0.6841063217763811
910/3780 0.150 0.082 1.0 MinMaxScaler() 0 -> 0.5086435998995427
911/3780 0.150 0.104 scale StandardScaler() 0 -> 0.4970382697102093
912/3780 0.150 0.104 scale MinMaxScaler() 0 -> 0.49626944022076686
913/3780 0.150 0.104 auto StandardScaler() 0 -> 0.4970382697102092
914/3780 0.150 0.104 auto MinMaxScaler() 0 -> 0.5848036454143498
915/3780 0.150 0.104 0.01 StandardScaler() 0 -> 0.5435337006202062
916/3780 0.150 0.104 0.01 MinMaxScaler() 0 -> 0.6949578397508206
917/3780 0.150 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5069843745656165
918/3780 0.150 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6417588329710736
919/3780 0.150 0.104 0.1 StandardScaler() 0 -> 0.49729145782942147
920/3780 0.150 0.104 0.1 MinMaxScaler() 0 -> 0.5805686537299725
921/3780 0.150 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5301902393890039
922/3780 0.150 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5362820411301761
923/3780 0.150 0.104 1.0 StandardScaler() 0 -> 0.6678637314227389
924/3780 0.150 0.104 1.0 MinMaxScaler() 0 -> 0.5046983277437187
925/3780 0.150 0.132 scale StandardScaler() 0 -> 0.49318111335702747
926/3780 0.150 0.132 scale MinMaxScaler() 0 -> 0.49318901977765844
927/3780 0.150 0.132 auto StandardScaler() 0 -> 0.4931811133570274
928/3780 0.150 0.132 auto MinMaxScaler() 0 -> 0.5737664137709668
929/3780 0.150 0.132 0.01 StandardScaler() 0 -> 0.5376404043142471
930/3780 0.150 0.132 0.01 MinMaxScaler() 0 -> 0.68253848888715
931/3780 0.150 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5029157037310973
932/3780 0.150 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6298301472744351
933/3780 0.150 0.132 0.1 StandardScaler() 0 -> 0.49341422120031303
934/3780 0.150 0.132 0.1 MinMaxScaler() 0 -> 0.5697836444883179
935/3780 0.150 0.132 0.31622776601683794 StandardScaler() 0 -> 0.518179339960818
936/3780 0.150 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5313748715096976
937/3780 0.150 0.132 1.0 StandardScaler() 0 -> 0.6494878241188274
938/3780 0.150 0.132 1.0 MinMaxScaler() 0 -> 0.5015997747668312
939/3780 0.150 0.168 scale StandardScaler() 0 -> 0.4901200248556632
940/3780 0.150 0.168 scale MinMaxScaler() 0 -> 0.4900034055824592
941/3780 0.150 0.168 auto StandardScaler() 0 -> 0.49012002485566314
942/3780 0.150 0.168 auto MinMaxScaler() 0 -> 0.5649697968213517
943/3780 0.150 0.168 0.01 StandardScaler() 0 -> 0.5311519307569617
944/3780 0.150 0.168 0.01 MinMaxScaler() 0 -> 0.6714322285874764
945/3780 0.150 0.168 0.03162277660168379 StandardScaler() 0 -> 0.49991595621033835
946/3780 0.150 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.6169195404222786
947/3780 0.150 0.168 0.1 StandardScaler() 0 -> 0.4896732030205985
948/3780 0.150 0.168 0.1 MinMaxScaler() 0 -> 0.5614346413440069
949/3780 0.150 0.168 0.31622776601683794 StandardScaler() 0 -> 0.506915218168367
950/3780 0.150 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5264276159422502
951/3780 0.150 0.168 1.0 StandardScaler() 0 -> 0.6295151766422915
952/3780 0.150 0.168 1.0 MinMaxScaler() 0 -> 0.4987938816614557
953/3780 0.150 0.213 scale StandardScaler() 0 -> 0.48647249398612286
954/3780 0.150 0.213 scale MinMaxScaler() 0 -> 0.4876272544906244
955/3780 0.150 0.213 auto StandardScaler() 0 -> 0.48647249398612297
956/3780 0.150 0.213 auto MinMaxScaler() 0 -> 0.5579598671105571
957/3780 0.150 0.213 0.01 StandardScaler() 0 -> 0.5261066342116101
958/3780 0.150 0.213 0.01 MinMaxScaler() 0 -> 0.6611032828888032
959/3780 0.150 0.213 0.03162277660168379 StandardScaler() 0 -> 0.497106362922074
960/3780 0.150 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.6029603361271308
961/3780 0.150 0.213 0.1 StandardScaler() 0 -> 0.48594246875798713
962/3780 0.150 0.213 0.1 MinMaxScaler() 0 -> 0.5554671530520615
963/3780 0.150 0.213 0.31622776601683794 StandardScaler() 0 -> 0.49737765295231934
964/3780 0.150 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5222958148536215
965/3780 0.150 0.213 1.0 StandardScaler() 0 -> 0.6085754909978162
966/3780 0.150 0.213 1.0 MinMaxScaler() 0 -> 0.496719212346216
967/3780 0.150 0.270 scale StandardScaler() 0 -> 0.4832069144128952
968/3780 0.150 0.270 scale MinMaxScaler() 0 -> 0.485450996806515
969/3780 0.150 0.270 auto StandardScaler() 0 -> 0.48320691441289515
970/3780 0.150 0.270 auto MinMaxScaler() 0 -> 0.5531650582518511
971/3780 0.150 0.270 0.01 StandardScaler() 0 -> 0.5220617498803929
972/3780 0.150 0.270 0.01 MinMaxScaler() 0 -> 0.6509539605766954
973/3780 0.150 0.270 0.03162277660168379 StandardScaler() 0 -> 0.49517995316512414
974/3780 0.150 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5897320886282463
975/3780 0.150 0.270 0.1 StandardScaler() 0 -> 0.4825377653004561
976/3780 0.150 0.270 0.1 MinMaxScaler() 0 -> 0.5506237402116718
977/3780 0.150 0.270 0.31622776601683794 StandardScaler() 0 -> 0.48896241781055166
978/3780 0.150 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5179493827471463
979/3780 0.150 0.270 1.0 StandardScaler() 0 -> 0.5877011741018526
980/3780 0.150 0.270 1.0 MinMaxScaler() 0 -> 0.49479234359274255
981/3780 0.150 0.342 scale StandardScaler() 0 -> 0.4808912077185837
982/3780 0.150 0.342 scale MinMaxScaler() 0 -> 0.48357929358250523
983/3780 0.150 0.342 auto StandardScaler() 0 -> 0.48089120771858385
984/3780 0.150 0.342 auto MinMaxScaler() 0 -> 0.5490648490551552
985/3780 0.150 0.342 0.01 StandardScaler() 0 -> 0.5175733436251949
986/3780 0.150 0.342 0.01 MinMaxScaler() 0 -> 0.6395738393071916
987/3780 0.150 0.342 0.03162277660168379 StandardScaler() 0 -> 0.4935923250729868
988/3780 0.150 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5789909151214362
989/3780 0.150 0.342 0.1 StandardScaler() 0 -> 0.48023567509902615
990/3780 0.150 0.342 0.1 MinMaxScaler() 0 -> 0.5468573241539599
991/3780 0.150 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4812751024137341
992/3780 0.150 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5142558925926639
993/3780 0.150 0.342 1.0 StandardScaler() 0 -> 0.5667816516761629
994/3780 0.150 0.342 1.0 MinMaxScaler() 0 -> 0.49352736329719943
995/3780 0.150 0.434 scale StandardScaler() 0 -> 0.47873382950568805
996/3780 0.150 0.434 scale MinMaxScaler() 0 -> 0.48169772250393955
997/3780 0.150 0.434 auto StandardScaler() 0 -> 0.4787338295056882
998/3780 0.150 0.434 auto MinMaxScaler() 0 -> 0.5455468605849126
999/3780 0.150 0.434 0.01 StandardScaler() 0 -> 0.513622691997934
1000/3780 0.150 0.434 0.01 MinMaxScaler() 0 -> 0.6269091602815983
1001/3780 0.150 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49253126103378286
1002/3780 0.150 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5696392288378148
1003/3780 0.150 0.434 0.1 StandardScaler() 0 -> 0.47814567229818516
1004/3780 0.150 0.434 0.1 MinMaxScaler() 0 -> 0.543073880397439
1005/3780 0.150 0.434 0.31622776601683794 StandardScaler() 0 -> 0.47504683848948676
1006/3780 0.150 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5109382928575354
1007/3780 0.150 0.434 1.0 StandardScaler() 0 -> 0.5468148185845181
1008/3780 0.150 0.434 1.0 MinMaxScaler() 0 -> 0.49264897613588426
1009/3780 0.150 0.551 scale StandardScaler() 0 -> 0.4769270408811866
1010/3780 0.150 0.551 scale MinMaxScaler() 0 -> 0.4804607175525372
1011/3780 0.150 0.551 auto StandardScaler() 0 -> 0.4769270408811867
1012/3780 0.150 0.551 auto MinMaxScaler() 0 -> 0.5423587387250485
1013/3780 0.150 0.551 0.01 StandardScaler() 0 -> 0.5094084504375601
1014/3780 0.150 0.551 0.01 MinMaxScaler() 0 -> 0.6139563041776123
1015/3780 0.150 0.551 0.03162277660168379 StandardScaler() 0 -> 0.49130929896994974
1016/3780 0.150 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5631308291766703
1017/3780 0.150 0.551 0.1 StandardScaler() 0 -> 0.4765916627551415
1018/3780 0.150 0.551 0.1 MinMaxScaler() 0 -> 0.5400579979493544
1019/3780 0.150 0.551 0.31622776601683794 StandardScaler() 0 -> 0.47010283430693756
1020/3780 0.150 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5081980350265612
1021/3780 0.150 0.551 1.0 StandardScaler() 0 -> 0.5286017987844219
1022/3780 0.150 0.551 1.0 MinMaxScaler() 0 -> 0.49104389493679196
1023/3780 0.150 0.700 scale StandardScaler() 0 -> 0.47620811153385717
1024/3780 0.150 0.700 scale MinMaxScaler() 0 -> 0.47843846661760886
1025/3780 0.150 0.700 auto StandardScaler() 0 -> 0.4762081115338573
1026/3780 0.150 0.700 auto MinMaxScaler() 0 -> 0.5392703458392427
1027/3780 0.150 0.700 0.01 StandardScaler() 0 -> 0.5068691170163052
1028/3780 0.150 0.700 0.01 MinMaxScaler() 0 -> 0.6001648241830132
1029/3780 0.150 0.700 0.03162277660168379 StandardScaler() 0 -> 0.4898990756016975
1030/3780 0.150 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5593605929730693
1031/3780 0.150 0.700 0.1 StandardScaler() 0 -> 0.4753741855538942
1032/3780 0.150 0.700 0.1 MinMaxScaler() 0 -> 0.5366654296896606
1033/3780 0.150 0.700 0.31622776601683794 StandardScaler() 0 -> 0.4668009175188874
1034/3780 0.150 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5054171284667223
1035/3780 0.150 0.700 1.0 StandardScaler() 0 -> 0.5121066390561443
1036/3780 0.150 0.700 1.0 MinMaxScaler() 0 -> 0.4897732225113205
1037/3780 0.150 0.888 scale StandardScaler() 0 -> 0.47506860372145693
1038/3780 0.150 0.888 scale MinMaxScaler() 0 -> 0.47749814392551665
1039/3780 0.150 0.888 auto StandardScaler() 0 -> 0.4750686037214565
1040/3780 0.150 0.888 auto MinMaxScaler() 0 -> 0.5358562435248725
1041/3780 0.150 0.888 0.01 StandardScaler() 0 -> 0.5038152104119371
1042/3780 0.150 0.888 0.01 MinMaxScaler() 0 -> 0.5876570708650833
1043/3780 0.150 0.888 0.03162277660168379 StandardScaler() 0 -> 0.48799791936127707
1044/3780 0.150 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5553591827595459
1045/3780 0.150 0.888 0.1 StandardScaler() 0 -> 0.4741118939815085
1046/3780 0.150 0.888 0.1 MinMaxScaler() 0 -> 0.533020349052915
1047/3780 0.150 0.888 0.31622776601683794 StandardScaler() 0 -> 0.46494528882896297
1048/3780 0.150 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5027297991048522
1049/3780 0.150 0.888 1.0 StandardScaler() 0 -> 0.4999584746889489
1050/3780 0.150 0.888 1.0 MinMaxScaler() 0 -> 0.48814899038926035
1051/3780 0.150 1.126 scale StandardScaler() 0 -> 0.4741280987017496
1052/3780 0.150 1.126 scale MinMaxScaler() 0 -> 0.47685615420350186
1053/3780 0.150 1.126 auto StandardScaler() 0 -> 0.4741280987017494
1054/3780 0.150 1.126 auto MinMaxScaler() 0 -> 0.5320580436337722
1055/3780 0.150 1.126 0.01 StandardScaler() 0 -> 0.5014960456916672
1056/3780 0.150 1.126 0.01 MinMaxScaler() 0 -> 0.5772930162900732
1057/3780 0.150 1.126 0.03162277660168379 StandardScaler() 0 -> 0.4860234378700706
1058/3780 0.150 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5530238104825556
1059/3780 0.150 1.126 0.1 StandardScaler() 0 -> 0.47337652020257526
1060/3780 0.150 1.126 0.1 MinMaxScaler() 0 -> 0.5293101694457102
1061/3780 0.150 1.126 0.31622776601683794 StandardScaler() 0 -> 0.46518817133613705
1062/3780 0.150 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.49987317805787645
1063/3780 0.150 1.126 1.0 StandardScaler() 0 -> 0.49393624417801735
1064/3780 0.150 1.126 1.0 MinMaxScaler() 0 -> 0.4864931342112741
1065/3780 0.150 1.429 scale StandardScaler() 0 -> 0.473845116067809
1066/3780 0.150 1.429 scale MinMaxScaler() 0 -> 0.47570525486931636
1067/3780 0.150 1.429 auto StandardScaler() 0 -> 0.4738451160678088
1068/3780 0.150 1.429 auto MinMaxScaler() 0 -> 0.5286756661095272
1069/3780 0.150 1.429 0.01 StandardScaler() 0 -> 0.500008255948483
1070/3780 0.150 1.429 0.01 MinMaxScaler() 0 -> 0.5689617661727189
1071/3780 0.150 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48477423628153066
1072/3780 0.150 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5509841268976484
1073/3780 0.150 1.429 0.1 StandardScaler() 0 -> 0.4731963817612281
1074/3780 0.150 1.429 0.1 MinMaxScaler() 0 -> 0.5264318796521769
1075/3780 0.150 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4663550807703242
1076/3780 0.150 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.4983834894852628
1077/3780 0.150 1.429 1.0 StandardScaler() 0 -> 0.4903897296278574
1078/3780 0.150 1.429 1.0 MinMaxScaler() 0 -> 0.4849197355209685
1079/3780 0.150 1.814 scale StandardScaler() 0 -> 0.47393278267081573
1080/3780 0.150 1.814 scale MinMaxScaler() 0 -> 0.4745440121093978
1081/3780 0.150 1.814 auto StandardScaler() 0 -> 0.47393278267081557
1082/3780 0.150 1.814 auto MinMaxScaler() 0 -> 0.5257241380004406
1083/3780 0.150 1.814 0.01 StandardScaler() 0 -> 0.49839751872294763
1084/3780 0.150 1.814 0.01 MinMaxScaler() 0 -> 0.5636146794814884
1085/3780 0.150 1.814 0.03162277660168379 StandardScaler() 0 -> 0.48325191141179463
1086/3780 0.150 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5492530529837013
1087/3780 0.150 1.814 0.1 StandardScaler() 0 -> 0.472654340663851
1088/3780 0.150 1.814 0.1 MinMaxScaler() 0 -> 0.5227572386450999
1089/3780 0.150 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4679767149079122
1090/3780 0.150 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.49710085945383736
1091/3780 0.150 1.814 1.0 StandardScaler() 0 -> 0.4885890337742673
1092/3780 0.150 1.814 1.0 MinMaxScaler() 0 -> 0.4840312724380596
1093/3780 0.150 2.302 scale StandardScaler() 0 -> 0.47356650075457324
1094/3780 0.150 2.302 scale MinMaxScaler() 0 -> 0.47368789227859986
1095/3780 0.150 2.302 auto StandardScaler() 0 -> 0.47356650075457346
1096/3780 0.150 2.302 auto MinMaxScaler() 0 -> 0.5219685704930238
1097/3780 0.150 2.302 0.01 StandardScaler() 0 -> 0.497990289114262
1098/3780 0.150 2.302 0.01 MinMaxScaler() 0 -> 0.5600387096179099
1099/3780 0.150 2.302 0.03162277660168379 StandardScaler() 0 -> 0.48254159866203644
1100/3780 0.150 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5471867358232555
1101/3780 0.150 2.302 0.1 StandardScaler() 0 -> 0.4725680716120635
1102/3780 0.150 2.302 0.1 MinMaxScaler() 0 -> 0.5192109362142929
1103/3780 0.150 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4711691148711598
1104/3780 0.150 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.49648483656858006
1105/3780 0.150 2.302 1.0 StandardScaler() 0 -> 0.4884315364546543
1106/3780 0.150 2.302 1.0 MinMaxScaler() 0 -> 0.4829000024974053
1107/3780 0.150 2.921 scale StandardScaler() 0 -> 0.4736815642340407
1108/3780 0.150 2.921 scale MinMaxScaler() 0 -> 0.4735714053598028
1109/3780 0.150 2.921 auto StandardScaler() 0 -> 0.47368156423404023
1110/3780 0.150 2.921 auto MinMaxScaler() 0 -> 0.5183344564679059
1111/3780 0.150 2.921 0.01 StandardScaler() 0 -> 0.4972386512658655
1112/3780 0.150 2.921 0.01 MinMaxScaler() 0 -> 0.5570602955058117
1113/3780 0.150 2.921 0.03162277660168379 StandardScaler() 0 -> 0.48240403605163135
1114/3780 0.150 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5453606538180708
1115/3780 0.150 2.921 0.1 StandardScaler() 0 -> 0.4742012899802497
1116/3780 0.150 2.921 0.1 MinMaxScaler() 0 -> 0.5159551364261725
1117/3780 0.150 2.921 0.31622776601683794 StandardScaler() 0 -> 0.47663389832489506
1118/3780 0.150 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.4961893059785439
1119/3780 0.150 2.921 1.0 StandardScaler() 0 -> 0.48820614022722736
1120/3780 0.150 2.921 1.0 MinMaxScaler() 0 -> 0.4823146552400221
1121/3780 0.150 3.707 scale StandardScaler() 0 -> 0.47572586670126754
1122/3780 0.150 3.707 scale MinMaxScaler() 0 -> 0.4742109734459188
1123/3780 0.150 3.707 auto StandardScaler() 0 -> 0.4757258667012678
1124/3780 0.150 3.707 auto MinMaxScaler() 0 -> 0.5152295809772239
1125/3780 0.150 3.707 0.01 StandardScaler() 0 -> 0.4967371894405825
1126/3780 0.150 3.707 0.01 MinMaxScaler() 0 -> 0.5553590244950554
1127/3780 0.150 3.707 0.03162277660168379 StandardScaler() 0 -> 0.4816737489570803
1128/3780 0.150 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5428604944241949
1129/3780 0.150 3.707 0.1 StandardScaler() 0 -> 0.4769689831392863
1130/3780 0.150 3.707 0.1 MinMaxScaler() 0 -> 0.5126870373842591
1131/3780 0.150 3.707 0.31622776601683794 StandardScaler() 0 -> 0.48237699376053955
1132/3780 0.150 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4957786898593471
1133/3780 0.150 3.707 1.0 StandardScaler() 0 -> 0.4882424878098293
1134/3780 0.150 3.707 1.0 MinMaxScaler() 0 -> 0.4815579548966083
1135/3780 0.150 4.703 scale StandardScaler() 0 -> 0.4788545795754562
1136/3780 0.150 4.703 scale MinMaxScaler() 0 -> 0.4766535364704172
1137/3780 0.150 4.703 auto StandardScaler() 0 -> 0.4788545795754556
1138/3780 0.150 4.703 auto MinMaxScaler() 0 -> 0.5120574789766281
1139/3780 0.150 4.703 0.01 StandardScaler() 0 -> 0.49589769608582124
1140/3780 0.150 4.703 0.01 MinMaxScaler() 0 -> 0.5541923837771088
1141/3780 0.150 4.703 0.03162277660168379 StandardScaler() 0 -> 0.48147471908636846
1142/3780 0.150 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5406160028596335
1143/3780 0.150 4.703 0.1 StandardScaler() 0 -> 0.4792965626482035
1144/3780 0.150 4.703 0.1 MinMaxScaler() 0 -> 0.5099254359531572
1145/3780 0.150 4.703 0.31622776601683794 StandardScaler() 0 -> 0.48740977716021444
1146/3780 0.150 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.4952169876316442
1147/3780 0.150 4.703 1.0 StandardScaler() 0 -> 0.4883692277472916
1148/3780 0.150 4.703 1.0 MinMaxScaler() 0 -> 0.48139013930488717
1149/3780 0.150 5.968 scale StandardScaler() 0 -> 0.4813761836558466
1150/3780 0.150 5.968 scale MinMaxScaler() 0 -> 0.47981296629022924
1151/3780 0.150 5.968 auto StandardScaler() 0 -> 0.4813761836558467
1152/3780 0.150 5.968 auto MinMaxScaler() 0 -> 0.5094927474862979
1153/3780 0.150 5.968 0.01 StandardScaler() 0 -> 0.4959510383682107
1154/3780 0.150 5.968 0.01 MinMaxScaler() 0 -> 0.5532817389598674
1155/3780 0.150 5.968 0.03162277660168379 StandardScaler() 0 -> 0.48183569020548545
1156/3780 0.150 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5379071703112998
1157/3780 0.150 5.968 0.1 StandardScaler() 0 -> 0.4832420267286275
1158/3780 0.150 5.968 0.1 MinMaxScaler() 0 -> 0.5076399164407766
1159/3780 0.150 5.968 0.31622776601683794 StandardScaler() 0 -> 0.49424252154256904
1160/3780 0.150 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.4943398867760133
1161/3780 0.150 5.968 1.0 StandardScaler() 0 -> 0.4885410293563699
1162/3780 0.150 5.968 1.0 MinMaxScaler() 0 -> 0.48174328510264885
1163/3780 0.150 7.574 scale StandardScaler() 0 -> 0.48593350110634764
1164/3780 0.150 7.574 scale MinMaxScaler() 0 -> 0.4823192075323564
1165/3780 0.150 7.574 auto StandardScaler() 0 -> 0.48593350110634853
1166/3780 0.150 7.574 auto MinMaxScaler() 0 -> 0.5072800507215756
1167/3780 0.150 7.574 0.01 StandardScaler() 0 -> 0.4953923203229891
1168/3780 0.150 7.574 0.01 MinMaxScaler() 0 -> 0.5522212974477094
1169/3780 0.150 7.574 0.03162277660168379 StandardScaler() 0 -> 0.48182574582291626
1170/3780 0.150 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5348200812613879
1171/3780 0.150 7.574 0.1 StandardScaler() 0 -> 0.48826781782256123
1172/3780 0.150 7.574 0.1 MinMaxScaler() 0 -> 0.5045179162113432
1173/3780 0.150 7.574 0.31622776601683794 StandardScaler() 0 -> 0.503011010891877
1174/3780 0.150 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.49394024884101534
1175/3780 0.150 7.574 1.0 StandardScaler() 0 -> 0.4886696413631289
1176/3780 0.150 7.574 1.0 MinMaxScaler() 0 -> 0.4814535712728094
1177/3780 0.150 9.611 scale StandardScaler() 0 -> 0.4917389273368058
1178/3780 0.150 9.611 scale MinMaxScaler() 0 -> 0.4852129164659556
1179/3780 0.150 9.611 auto StandardScaler() 0 -> 0.49173892733680774
1180/3780 0.150 9.611 auto MinMaxScaler() 0 -> 0.5040317701365378
1181/3780 0.150 9.611 0.01 StandardScaler() 0 -> 0.4944212197921128
1182/3780 0.150 9.611 0.01 MinMaxScaler() 0 -> 0.5512628090042445
1183/3780 0.150 9.611 0.03162277660168379 StandardScaler() 0 -> 0.48092988380549023
1184/3780 0.150 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5312613107476654
1185/3780 0.150 9.611 0.1 StandardScaler() 0 -> 0.4959742293404714
1186/3780 0.150 9.611 0.1 MinMaxScaler() 0 -> 0.5025388628902671
1187/3780 0.150 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5105053063889197
1188/3780 0.150 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4930951734257918
1189/3780 0.150 9.611 1.0 StandardScaler() 0 -> 0.488710254650311
1190/3780 0.150 9.611 1.0 MinMaxScaler() 0 -> 0.481939767472183
1191/3780 0.150 12.196 scale StandardScaler() 0 -> 0.49972191327209964
1192/3780 0.150 12.196 scale MinMaxScaler() 0 -> 0.48852174749908933
1193/3780 0.150 12.196 auto StandardScaler() 0 -> 0.4997219132721004
1194/3780 0.150 12.196 auto MinMaxScaler() 0 -> 0.5023740888189695
1195/3780 0.150 12.196 0.01 StandardScaler() 0 -> 0.4939397715184546
1196/3780 0.150 12.196 0.01 MinMaxScaler() 0 -> 0.5507406929324437
1197/3780 0.150 12.196 0.03162277660168379 StandardScaler() 0 -> 0.48125016759465417
1198/3780 0.150 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5282000943044153
1199/3780 0.150 12.196 0.1 StandardScaler() 0 -> 0.5070863176788782
1200/3780 0.150 12.196 0.1 MinMaxScaler() 0 -> 0.50076218602113
1201/3780 0.150 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5163236624397057
1202/3780 0.150 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.49226051009954697
1203/3780 0.150 12.196 1.0 StandardScaler() 0 -> 0.48871422035331946
1204/3780 0.150 12.196 1.0 MinMaxScaler() 0 -> 0.4821093595667448
1205/3780 0.150 15.476 scale StandardScaler() 0 -> 0.5111478216733605
1206/3780 0.150 15.476 scale MinMaxScaler() 0 -> 0.49346281133973663
1207/3780 0.150 15.476 auto StandardScaler() 0 -> 0.5111478216733557
1208/3780 0.150 15.476 auto MinMaxScaler() 0 -> 0.5007960456276991
1209/3780 0.150 15.476 0.01 StandardScaler() 0 -> 0.49337378767630535
1210/3780 0.150 15.476 0.01 MinMaxScaler() 0 -> 0.5491164630435109
1211/3780 0.150 15.476 0.03162277660168379 StandardScaler() 0 -> 0.4822551261874499
1212/3780 0.150 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5248479128961251
1213/3780 0.150 15.476 0.1 StandardScaler() 0 -> 0.5226318370516182
1214/3780 0.150 15.476 0.1 MinMaxScaler() 0 -> 0.5003778016870123
1215/3780 0.150 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5203974005081241
1216/3780 0.150 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.4912548867216282
1217/3780 0.150 15.476 1.0 StandardScaler() 0 -> 0.48871009192522247
1218/3780 0.150 15.476 1.0 MinMaxScaler() 0 -> 0.48219504514400574
1219/3780 0.150 19.638 scale StandardScaler() 0 -> 0.5269302336440983
1220/3780 0.150 19.638 scale MinMaxScaler() 0 -> 0.5022250955335424
1221/3780 0.150 19.638 auto StandardScaler() 0 -> 0.5269302336441016
1222/3780 0.150 19.638 auto MinMaxScaler() 0 -> 0.5005627669241635
1223/3780 0.150 19.638 0.01 StandardScaler() 0 -> 0.49204432329627484
1224/3780 0.150 19.638 0.01 MinMaxScaler() 0 -> 0.547908396431011
1225/3780 0.150 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4834150775372092
1226/3780 0.150 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5209607329536184
1227/3780 0.150 19.638 0.1 StandardScaler() 0 -> 0.541733314711514
1228/3780 0.150 19.638 0.1 MinMaxScaler() 0 -> 0.49995610896501375
1229/3780 0.150 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5241274153121327
1230/3780 0.150 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.49004645268029307
1231/3780 0.150 19.638 1.0 StandardScaler() 0 -> 0.48871009192522247
1232/3780 0.150 19.638 1.0 MinMaxScaler() 0 -> 0.4832969902417346
1233/3780 0.150 24.920 scale StandardScaler() 0 -> 0.547086345329965
1234/3780 0.150 24.920 scale MinMaxScaler() 0 -> 0.5133794953464874
1235/3780 0.150 24.920 auto StandardScaler() 0 -> 0.5470863453299581
1236/3780 0.150 24.920 auto MinMaxScaler() 0 -> 0.5000664824532209
1237/3780 0.150 24.920 0.01 StandardScaler() 0 -> 0.49003321586960147
1238/3780 0.150 24.920 0.01 MinMaxScaler() 0 -> 0.5461595561719338
1239/3780 0.150 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4853173860413204
1240/3780 0.150 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5179741321874974
1241/3780 0.150 24.920 0.1 StandardScaler() 0 -> 0.5638246911999372
1242/3780 0.150 24.920 0.1 MinMaxScaler() 0 -> 0.49923941015891743
1243/3780 0.150 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5276552466884729
1244/3780 0.150 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.488747246711483
1245/3780 0.150 24.920 1.0 StandardScaler() 0 -> 0.48871009192522247
1246/3780 0.150 24.920 1.0 MinMaxScaler() 0 -> 0.4847175687161294
1247/3780 0.150 31.623 scale StandardScaler() 0 -> 0.5704162690401869
1248/3780 0.150 31.623 scale MinMaxScaler() 0 -> 0.5273937401879646
1249/3780 0.150 31.623 auto StandardScaler() 0 -> 0.5704162690401927
1250/3780 0.150 31.623 auto MinMaxScaler() 0 -> 0.4992575660451018
1251/3780 0.150 31.623 0.01 StandardScaler() 0 -> 0.48857156388149026
1252/3780 0.150 31.623 0.01 MinMaxScaler() 0 -> 0.5443920052745889
1253/3780 0.150 31.623 0.03162277660168379 StandardScaler() 0 -> 0.48870376794496656
1254/3780 0.150 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5148745645808558
1255/3780 0.150 31.623 0.1 StandardScaler() 0 -> 0.5882653921286694
1256/3780 0.150 31.623 0.1 MinMaxScaler() 0 -> 0.498485351361548
1257/3780 0.150 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5300451822179655
1258/3780 0.150 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4880272575023242
1259/3780 0.150 31.623 1.0 StandardScaler() 0 -> 0.48871009192522247
1260/3780 0.150 31.623 1.0 MinMaxScaler() 0 -> 0.48644511029465604
1261/3780 0.200 0.032 scale StandardScaler() 0 -> 0.5289264495541057
1262/3780 0.200 0.032 scale MinMaxScaler() 0 -> 0.5221453597386172
1263/3780 0.200 0.032 auto StandardScaler() 0 -> 0.5289264495541058
1264/3780 0.200 0.032 auto MinMaxScaler() 0 -> 0.6384120029905612
1265/3780 0.200 0.032 0.01 StandardScaler() 0 -> 0.5889580862260789
1266/3780 0.200 0.032 0.01 MinMaxScaler() 0 -> 0.7444051417895602
1267/3780 0.200 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5403753106766717
1268/3780 0.200 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7001878678398309
1269/3780 0.200 0.032 0.1 StandardScaler() 0 -> 0.5305641173906068
1270/3780 0.200 0.032 0.1 MinMaxScaler() 0 -> 0.6341035875754382
1271/3780 0.200 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6048244302871563
1272/3780 0.200 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5761393243305757
1273/3780 0.200 0.032 1.0 StandardScaler() 0 -> 0.7373263573770837
1274/3780 0.200 0.032 1.0 MinMaxScaler() 0 -> 0.5317018484040312
1275/3780 0.200 0.040 scale StandardScaler() 0 -> 0.5199143453668541
1276/3780 0.200 0.040 scale MinMaxScaler() 0 -> 0.515115182549114
1277/3780 0.200 0.040 auto StandardScaler() 0 -> 0.5199143453668541
1278/3780 0.200 0.040 auto MinMaxScaler() 0 -> 0.6271476198279936
1279/3780 0.200 0.040 0.01 StandardScaler() 0 -> 0.5766947749470853
1280/3780 0.200 0.040 0.01 MinMaxScaler() 0 -> 0.738228469660076
1281/3780 0.200 0.040 0.03162277660168379 StandardScaler() 0 -> 0.530836682760326
1282/3780 0.200 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.6853784870947722
1283/3780 0.200 0.040 0.1 StandardScaler() 0 -> 0.5213176663770084
1284/3780 0.200 0.040 0.1 MinMaxScaler() 0 -> 0.6220528037613585
1285/3780 0.200 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5870605791810163
1286/3780 0.200 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5643417086071182
1287/3780 0.200 0.040 1.0 StandardScaler() 0 -> 0.7293707031877082
1288/3780 0.200 0.040 1.0 MinMaxScaler() 0 -> 0.5248613701634226
1289/3780 0.200 0.051 scale StandardScaler() 0 -> 0.512207140895094
1290/3780 0.200 0.051 scale MinMaxScaler() 0 -> 0.5092030094571908
1291/3780 0.200 0.051 auto StandardScaler() 0 -> 0.512207140895094
1292/3780 0.200 0.051 auto MinMaxScaler() 0 -> 0.6140637548695614
1293/3780 0.200 0.051 0.01 StandardScaler() 0 -> 0.5653436295600343
1294/3780 0.200 0.051 0.01 MinMaxScaler() 0 -> 0.730622858120828
1295/3780 0.200 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5243643723590026
1296/3780 0.200 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.669329955310198
1297/3780 0.200 0.051 0.1 StandardScaler() 0 -> 0.5134026274045879
1298/3780 0.200 0.051 0.1 MinMaxScaler() 0 -> 0.6093719532105119
1299/3780 0.200 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5703464538881268
1300/3780 0.200 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5540577125521019
1301/3780 0.200 0.051 1.0 StandardScaler() 0 -> 0.7195838023163431
1302/3780 0.200 0.051 1.0 MinMaxScaler() 0 -> 0.5190376366611161
1303/3780 0.200 0.065 scale StandardScaler() 0 -> 0.5063056781439742
1304/3780 0.200 0.065 scale MinMaxScaler() 0 -> 0.5043516978069668
1305/3780 0.200 0.065 auto StandardScaler() 0 -> 0.5063056781439742
1306/3780 0.200 0.065 auto MinMaxScaler() 0 -> 0.6010077070284446
1307/3780 0.200 0.065 0.01 StandardScaler() 0 -> 0.5562481745940379
1308/3780 0.200 0.065 0.01 MinMaxScaler() 0 -> 0.7213189727550651
1309/3780 0.200 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5178127381946701
1310/3780 0.200 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6544255889921954
1311/3780 0.200 0.065 0.1 StandardScaler() 0 -> 0.5071907518387196
1312/3780 0.200 0.065 0.1 MinMaxScaler() 0 -> 0.5959377713063903
1313/3780 0.200 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5553407690496067
1314/3780 0.200 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.546972440696833
1315/3780 0.200 0.065 1.0 StandardScaler() 0 -> 0.7076619978027049
1316/3780 0.200 0.065 1.0 MinMaxScaler() 0 -> 0.5138020843569768
1317/3780 0.200 0.082 scale StandardScaler() 0 -> 0.5012275276584343
1318/3780 0.200 0.082 scale MinMaxScaler() 0 -> 0.5002762364904975
1319/3780 0.200 0.082 auto StandardScaler() 0 -> 0.5012275276584343
1320/3780 0.200 0.082 auto MinMaxScaler() 0 -> 0.5878213695240767
1321/3780 0.200 0.082 0.01 StandardScaler() 0 -> 0.5484633164913756
1322/3780 0.200 0.082 0.01 MinMaxScaler() 0 -> 0.7101320339214604
1323/3780 0.200 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5124978413554663
1324/3780 0.200 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6420144433590127
1325/3780 0.200 0.082 0.1 StandardScaler() 0 -> 0.5017151651574899
1326/3780 0.200 0.082 0.1 MinMaxScaler() 0 -> 0.5831220793672043
1327/3780 0.200 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5418434117600643
1328/3780 0.200 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.540932257974457
1329/3780 0.200 0.082 1.0 StandardScaler() 0 -> 0.6933763161084453
1330/3780 0.200 0.082 1.0 MinMaxScaler() 0 -> 0.509660484228209
1331/3780 0.200 0.104 scale StandardScaler() 0 -> 0.4964613754871632
1332/3780 0.200 0.104 scale MinMaxScaler() 0 -> 0.49626491017041774
1333/3780 0.200 0.104 auto StandardScaler() 0 -> 0.4964613754871631
1334/3780 0.200 0.104 auto MinMaxScaler() 0 -> 0.5759427308625459
1335/3780 0.200 0.104 0.01 StandardScaler() 0 -> 0.5418265992370855
1336/3780 0.200 0.104 0.01 MinMaxScaler() 0 -> 0.6969232324151496
1337/3780 0.200 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5073684246140354
1338/3780 0.200 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.63096445747967
1339/3780 0.200 0.104 0.1 StandardScaler() 0 -> 0.49667663461559936
1340/3780 0.200 0.104 0.1 MinMaxScaler() 0 -> 0.5720319774054755
1341/3780 0.200 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5294628612797639
1342/3780 0.200 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5359778347956864
1343/3780 0.200 0.104 1.0 StandardScaler() 0 -> 0.6769705623990956
1344/3780 0.200 0.104 1.0 MinMaxScaler() 0 -> 0.5056936956629526
1345/3780 0.200 0.132 scale StandardScaler() 0 -> 0.4921100015676651
1346/3780 0.200 0.132 scale MinMaxScaler() 0 -> 0.4923461780251444
1347/3780 0.200 0.132 auto StandardScaler() 0 -> 0.4921100015676651
1348/3780 0.200 0.132 auto MinMaxScaler() 0 -> 0.5668003221645889
1349/3780 0.200 0.132 0.01 StandardScaler() 0 -> 0.5362052307664923
1350/3780 0.200 0.132 0.01 MinMaxScaler() 0 -> 0.6817151346654513
1351/3780 0.200 0.132 0.03162277660168379 StandardScaler() 0 -> 0.503407747195489
1352/3780 0.200 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.617797540211445
1353/3780 0.200 0.132 0.1 StandardScaler() 0 -> 0.49219504684192544
1354/3780 0.200 0.132 0.1 MinMaxScaler() 0 -> 0.5638499147084979
1355/3780 0.200 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5178524784088483
1356/3780 0.200 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5312911154480937
1357/3780 0.200 0.132 1.0 StandardScaler() 0 -> 0.6586805560770287
1358/3780 0.200 0.132 1.0 MinMaxScaler() 0 -> 0.5021882462185582
1359/3780 0.200 0.168 scale StandardScaler() 0 -> 0.4883646779791841
1360/3780 0.200 0.168 scale MinMaxScaler() 0 -> 0.4898528630672116
1361/3780 0.200 0.168 auto StandardScaler() 0 -> 0.48836467797918415
1362/3780 0.200 0.168 auto MinMaxScaler() 0 -> 0.560319850246182
1363/3780 0.200 0.168 0.01 StandardScaler() 0 -> 0.5312401820775237
1364/3780 0.200 0.168 0.01 MinMaxScaler() 0 -> 0.6657764217558019
1365/3780 0.200 0.168 0.03162277660168379 StandardScaler() 0 -> 0.49991303497557044
1366/3780 0.200 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.605427046521508
1367/3780 0.200 0.168 0.1 StandardScaler() 0 -> 0.4880736965541281
1368/3780 0.200 0.168 0.1 MinMaxScaler() 0 -> 0.5579097727323129
1369/3780 0.200 0.168 0.31622776601683794 StandardScaler() 0 -> 0.507081144251852
1370/3780 0.200 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5266622166923401
1371/3780 0.200 0.168 1.0 StandardScaler() 0 -> 0.6383277302393541
1372/3780 0.200 0.168 1.0 MinMaxScaler() 0 -> 0.499150200259288
1373/3780 0.200 0.213 scale StandardScaler() 0 -> 0.485389047667663
1374/3780 0.200 0.213 scale MinMaxScaler() 0 -> 0.48741087141547185
1375/3780 0.200 0.213 auto StandardScaler() 0 -> 0.48538904766766305
1376/3780 0.200 0.213 auto MinMaxScaler() 0 -> 0.5554960222173632
1377/3780 0.200 0.213 0.01 StandardScaler() 0 -> 0.5270024507648171
1378/3780 0.200 0.213 0.01 MinMaxScaler() 0 -> 0.6518064196994998
1379/3780 0.200 0.213 0.03162277660168379 StandardScaler() 0 -> 0.49692972744022956
1380/3780 0.200 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5923561685563532
1381/3780 0.200 0.213 0.1 StandardScaler() 0 -> 0.4849098087591035
1382/3780 0.200 0.213 0.1 MinMaxScaler() 0 -> 0.5531886789797156
1383/3780 0.200 0.213 0.31622776601683794 StandardScaler() 0 -> 0.4974412589265409
1384/3780 0.200 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.52283152841956
1385/3780 0.200 0.213 1.0 StandardScaler() 0 -> 0.6167120340381437
1386/3780 0.200 0.213 1.0 MinMaxScaler() 0 -> 0.4963275754506073
1387/3780 0.200 0.270 scale StandardScaler() 0 -> 0.4828437397023053
1388/3780 0.200 0.270 scale MinMaxScaler() 0 -> 0.4849616564109209
1389/3780 0.200 0.270 auto StandardScaler() 0 -> 0.48284373970230526
1390/3780 0.200 0.270 auto MinMaxScaler() 0 -> 0.5511974489565095
1391/3780 0.200 0.270 0.01 StandardScaler() 0 -> 0.5228531576532929
1392/3780 0.200 0.270 0.01 MinMaxScaler() 0 -> 0.6392044478936647
1393/3780 0.200 0.270 0.03162277660168379 StandardScaler() 0 -> 0.49495862990524264
1394/3780 0.200 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5805376079256995
1395/3780 0.200 0.270 0.1 StandardScaler() 0 -> 0.48202730170277697
1396/3780 0.200 0.270 0.1 MinMaxScaler() 0 -> 0.5491991618596536
1397/3780 0.200 0.270 0.31622776601683794 StandardScaler() 0 -> 0.4885376172617834
1398/3780 0.200 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5190977053531746
1399/3780 0.200 0.270 1.0 StandardScaler() 0 -> 0.5949448670567801
1400/3780 0.200 0.270 1.0 MinMaxScaler() 0 -> 0.49430049728241343
1401/3780 0.200 0.342 scale StandardScaler() 0 -> 0.4802059262114189
1402/3780 0.200 0.342 scale MinMaxScaler() 0 -> 0.4825828483360132
1403/3780 0.200 0.342 auto StandardScaler() 0 -> 0.48020592621141905
1404/3780 0.200 0.342 auto MinMaxScaler() 0 -> 0.5475580716283711
1405/3780 0.200 0.342 0.01 StandardScaler() 0 -> 0.5181040532103732
1406/3780 0.200 0.342 0.01 MinMaxScaler() 0 -> 0.6280862644676154
1407/3780 0.200 0.342 0.03162277660168379 StandardScaler() 0 -> 0.493033520005856
1408/3780 0.200 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5712430729391575
1409/3780 0.200 0.342 0.1 StandardScaler() 0 -> 0.47973574908165784
1410/3780 0.200 0.342 0.1 MinMaxScaler() 0 -> 0.54569729861093
1411/3780 0.200 0.342 0.31622776601683794 StandardScaler() 0 -> 0.48133671490963764
1412/3780 0.200 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5155079524354842
1413/3780 0.200 0.342 1.0 StandardScaler() 0 -> 0.5729633376863376
1414/3780 0.200 0.342 1.0 MinMaxScaler() 0 -> 0.4920205858904388
1415/3780 0.200 0.434 scale StandardScaler() 0 -> 0.478497284227637
1416/3780 0.200 0.434 scale MinMaxScaler() 0 -> 0.48051362154585014
1417/3780 0.200 0.434 auto StandardScaler() 0 -> 0.478497284227637
1418/3780 0.200 0.434 auto MinMaxScaler() 0 -> 0.5445291897294926
1419/3780 0.200 0.434 0.01 StandardScaler() 0 -> 0.5142101421276076
1420/3780 0.200 0.434 0.01 MinMaxScaler() 0 -> 0.6150550765299507
1421/3780 0.200 0.434 0.03162277660168379 StandardScaler() 0 -> 0.4908738560625394
1422/3780 0.200 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5648202144458662
1423/3780 0.200 0.434 0.1 StandardScaler() 0 -> 0.47792124518527374
1424/3780 0.200 0.434 0.1 MinMaxScaler() 0 -> 0.5424500456440269
1425/3780 0.200 0.434 0.31622776601683794 StandardScaler() 0 -> 0.4752620935435889
1426/3780 0.200 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5123722273894288
1427/3780 0.200 0.434 1.0 StandardScaler() 0 -> 0.5523739533678936
1428/3780 0.200 0.434 1.0 MinMaxScaler() 0 -> 0.49015547992037095
1429/3780 0.200 0.551 scale StandardScaler() 0 -> 0.47655289716749144
1430/3780 0.200 0.551 scale MinMaxScaler() 0 -> 0.4782009564142931
1431/3780 0.200 0.551 auto StandardScaler() 0 -> 0.4765528971674915
1432/3780 0.200 0.551 auto MinMaxScaler() 0 -> 0.541559193764856
1433/3780 0.200 0.551 0.01 StandardScaler() 0 -> 0.5107968181122979
1434/3780 0.200 0.551 0.01 MinMaxScaler() 0 -> 0.6027114183820544
1435/3780 0.200 0.551 0.03162277660168379 StandardScaler() 0 -> 0.48951945926307266
1436/3780 0.200 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5605845833989139
1437/3780 0.200 0.551 0.1 StandardScaler() 0 -> 0.4759212696785171
1438/3780 0.200 0.551 0.1 MinMaxScaler() 0 -> 0.5392836873669132
1439/3780 0.200 0.551 0.31622776601683794 StandardScaler() 0 -> 0.47044155111135316
1440/3780 0.200 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5091044968478544
1441/3780 0.200 0.551 1.0 StandardScaler() 0 -> 0.5332133408473934
1442/3780 0.200 0.551 1.0 MinMaxScaler() 0 -> 0.4887757677621087
1443/3780 0.200 0.700 scale StandardScaler() 0 -> 0.47507294318974314
1444/3780 0.200 0.700 scale MinMaxScaler() 0 -> 0.47642146091828524
1445/3780 0.200 0.700 auto StandardScaler() 0 -> 0.4750729431897432
1446/3780 0.200 0.700 auto MinMaxScaler() 0 -> 0.538439052308754
1447/3780 0.200 0.700 0.01 StandardScaler() 0 -> 0.508134533384574
1448/3780 0.200 0.700 0.01 MinMaxScaler() 0 -> 0.5899544550728798
1449/3780 0.200 0.700 0.03162277660168379 StandardScaler() 0 -> 0.48823649843026357
1450/3780 0.200 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5571064055002326
1451/3780 0.200 0.700 0.1 StandardScaler() 0 -> 0.47429578811916273
1452/3780 0.200 0.700 0.1 MinMaxScaler() 0 -> 0.5360267971902891
1453/3780 0.200 0.700 0.31622776601683794 StandardScaler() 0 -> 0.46683467345016777
1454/3780 0.200 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5058809439150638
1455/3780 0.200 0.700 1.0 StandardScaler() 0 -> 0.5153334719465917
1456/3780 0.200 0.700 1.0 MinMaxScaler() 0 -> 0.4871545106980932
1457/3780 0.200 0.888 scale StandardScaler() 0 -> 0.4740308329087706
1458/3780 0.200 0.888 scale MinMaxScaler() 0 -> 0.4752141155389313
1459/3780 0.200 0.888 auto StandardScaler() 0 -> 0.4740308329087708
1460/3780 0.200 0.888 auto MinMaxScaler() 0 -> 0.5357432781308814
1461/3780 0.200 0.888 0.01 StandardScaler() 0 -> 0.5052097072069671
1462/3780 0.200 0.888 0.01 MinMaxScaler() 0 -> 0.5787255595078347
1463/3780 0.200 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4870426474163913
1464/3780 0.200 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5541721185678979
1465/3780 0.200 0.888 0.1 StandardScaler() 0 -> 0.4730817236467117
1466/3780 0.200 0.888 0.1 MinMaxScaler() 0 -> 0.5334826518586976
1467/3780 0.200 0.888 0.31622776601683794 StandardScaler() 0 -> 0.4647569252874031
1468/3780 0.200 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5029604782241067
1469/3780 0.200 0.888 1.0 StandardScaler() 0 -> 0.5034427119614424
1470/3780 0.200 0.888 1.0 MinMaxScaler() 0 -> 0.48569521159191215
1471/3780 0.200 1.126 scale StandardScaler() 0 -> 0.4730974273495605
1472/3780 0.200 1.126 scale MinMaxScaler() 0 -> 0.4740988821526197
1473/3780 0.200 1.126 auto StandardScaler() 0 -> 0.47309742734956006
1474/3780 0.200 1.126 auto MinMaxScaler() 0 -> 0.5328536311344133
1475/3780 0.200 1.126 0.01 StandardScaler() 0 -> 0.502240397546624
1476/3780 0.200 1.126 0.01 MinMaxScaler() 0 -> 0.5708257312255216
1477/3780 0.200 1.126 0.03162277660168379 StandardScaler() 0 -> 0.4854226895609246
1478/3780 0.200 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5521577231539677
1479/3780 0.200 1.126 0.1 StandardScaler() 0 -> 0.4715964906877254
1480/3780 0.200 1.126 0.1 MinMaxScaler() 0 -> 0.5298432902589374
1481/3780 0.200 1.126 0.31622776601683794 StandardScaler() 0 -> 0.46410003321985577
1482/3780 0.200 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5004542246086617
1483/3780 0.200 1.126 1.0 StandardScaler() 0 -> 0.49790549218356706
1484/3780 0.200 1.126 1.0 MinMaxScaler() 0 -> 0.48413335151442355
1485/3780 0.200 1.429 scale StandardScaler() 0 -> 0.4718903574391624
1486/3780 0.200 1.429 scale MinMaxScaler() 0 -> 0.473796754528573
1487/3780 0.200 1.429 auto StandardScaler() 0 -> 0.47189035743916197
1488/3780 0.200 1.429 auto MinMaxScaler() 0 -> 0.5289131178594094
1489/3780 0.200 1.429 0.01 StandardScaler() 0 -> 0.49972273545243406
1490/3780 0.200 1.429 0.01 MinMaxScaler() 0 -> 0.564627590792852
1491/3780 0.200 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48456365375734606
1492/3780 0.200 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.550113740772713
1493/3780 0.200 1.429 0.1 StandardScaler() 0 -> 0.47071571042500165
1494/3780 0.200 1.429 0.1 MinMaxScaler() 0 -> 0.5264132549235963
1495/3780 0.200 1.429 0.31622776601683794 StandardScaler() 0 -> 0.46457815674494857
1496/3780 0.200 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.49879815534273786
1497/3780 0.200 1.429 1.0 StandardScaler() 0 -> 0.4940765999807944
1498/3780 0.200 1.429 1.0 MinMaxScaler() 0 -> 0.4830593428296712
1499/3780 0.200 1.814 scale StandardScaler() 0 -> 0.4713196289159833
1500/3780 0.200 1.814 scale MinMaxScaler() 0 -> 0.4733057275772599
1501/3780 0.200 1.814 auto StandardScaler() 0 -> 0.4713196289159833
1502/3780 0.200 1.814 auto MinMaxScaler() 0 -> 0.5258097179522315
1503/3780 0.200 1.814 0.01 StandardScaler() 0 -> 0.4981311806172551
1504/3780 0.200 1.814 0.01 MinMaxScaler() 0 -> 0.5612611194615855
1505/3780 0.200 1.814 0.03162277660168379 StandardScaler() 0 -> 0.4828029688679259
1506/3780 0.200 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5483157253105895
1507/3780 0.200 1.814 0.1 StandardScaler() 0 -> 0.4703197804431604
1508/3780 0.200 1.814 0.1 MinMaxScaler() 0 -> 0.5231011178520296
1509/3780 0.200 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4656283035909485
1510/3780 0.200 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.4973281657828388
1511/3780 0.200 1.814 1.0 StandardScaler() 0 -> 0.4921775761996747
1512/3780 0.200 1.814 1.0 MinMaxScaler() 0 -> 0.48245896858977283
1513/3780 0.200 2.302 scale StandardScaler() 0 -> 0.47124308297597234
1514/3780 0.200 2.302 scale MinMaxScaler() 0 -> 0.4731175783832373
1515/3780 0.200 2.302 auto StandardScaler() 0 -> 0.4712430829759721
1516/3780 0.200 2.302 auto MinMaxScaler() 0 -> 0.5224510985926818
1517/3780 0.200 2.302 0.01 StandardScaler() 0 -> 0.4969894866297111
1518/3780 0.200 2.302 0.01 MinMaxScaler() 0 -> 0.5583295072918645
1519/3780 0.200 2.302 0.03162277660168379 StandardScaler() 0 -> 0.4823825669350235
1520/3780 0.200 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5466040583599643
1521/3780 0.200 2.302 0.1 StandardScaler() 0 -> 0.4707971174342463
1522/3780 0.200 2.302 0.1 MinMaxScaler() 0 -> 0.5198367748680749
1523/3780 0.200 2.302 0.31622776601683794 StandardScaler() 0 -> 0.469521345982548
1524/3780 0.200 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.4963888505224317
1525/3780 0.200 2.302 1.0 StandardScaler() 0 -> 0.49190608521475365
1526/3780 0.200 2.302 1.0 MinMaxScaler() 0 -> 0.4814827366590144
1527/3780 0.200 2.921 scale StandardScaler() 0 -> 0.4723887668112403
1528/3780 0.200 2.921 scale MinMaxScaler() 0 -> 0.47396257760012944
1529/3780 0.200 2.921 auto StandardScaler() 0 -> 0.4723887668112405
1530/3780 0.200 2.921 auto MinMaxScaler() 0 -> 0.5192417609243355
1531/3780 0.200 2.921 0.01 StandardScaler() 0 -> 0.4960348007435287
1532/3780 0.200 2.921 0.01 MinMaxScaler() 0 -> 0.5560838998178851
1533/3780 0.200 2.921 0.03162277660168379 StandardScaler() 0 -> 0.48157318206807737
1534/3780 0.200 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.544971248446829
1535/3780 0.200 2.921 0.1 StandardScaler() 0 -> 0.47279594409913955
1536/3780 0.200 2.921 0.1 MinMaxScaler() 0 -> 0.5164375198249734
1537/3780 0.200 2.921 0.31622776601683794 StandardScaler() 0 -> 0.4742386788197163
1538/3780 0.200 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49566042005534583
1539/3780 0.200 2.921 1.0 StandardScaler() 0 -> 0.4916844036429275
1540/3780 0.200 2.921 1.0 MinMaxScaler() 0 -> 0.4805694174664987
1541/3780 0.200 3.707 scale StandardScaler() 0 -> 0.47462620215839163
1542/3780 0.200 3.707 scale MinMaxScaler() 0 -> 0.47502781530981303
1543/3780 0.200 3.707 auto StandardScaler() 0 -> 0.47462620215839185
1544/3780 0.200 3.707 auto MinMaxScaler() 0 -> 0.5158490968057771
1545/3780 0.200 3.707 0.01 StandardScaler() 0 -> 0.49500436146166304
1546/3780 0.200 3.707 0.01 MinMaxScaler() 0 -> 0.5545739538877905
1547/3780 0.200 3.707 0.03162277660168379 StandardScaler() 0 -> 0.48073093382078375
1548/3780 0.200 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5431370077739168
1549/3780 0.200 3.707 0.1 StandardScaler() 0 -> 0.47478353353628777
1550/3780 0.200 3.707 0.1 MinMaxScaler() 0 -> 0.5134230469835522
1551/3780 0.200 3.707 0.31622776601683794 StandardScaler() 0 -> 0.47881923969890844
1552/3780 0.200 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.49465391892655797
1553/3780 0.200 3.707 1.0 StandardScaler() 0 -> 0.4917338387403521
1554/3780 0.200 3.707 1.0 MinMaxScaler() 0 -> 0.48016412122658014
1555/3780 0.200 4.703 scale StandardScaler() 0 -> 0.4767103814371986
1556/3780 0.200 4.703 scale MinMaxScaler() 0 -> 0.4768087588092973
1557/3780 0.200 4.703 auto StandardScaler() 0 -> 0.4767103814371982
1558/3780 0.200 4.703 auto MinMaxScaler() 0 -> 0.5130082600883636
1559/3780 0.200 4.703 0.01 StandardScaler() 0 -> 0.4941082759447288
1560/3780 0.200 4.703 0.01 MinMaxScaler() 0 -> 0.5532443681560321
1561/3780 0.200 4.703 0.03162277660168379 StandardScaler() 0 -> 0.47987792880226965
1562/3780 0.200 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5407054139742226
1563/3780 0.200 4.703 0.1 StandardScaler() 0 -> 0.47639939735018383
1564/3780 0.200 4.703 0.1 MinMaxScaler() 0 -> 0.5108752362716562
1565/3780 0.200 4.703 0.31622776601683794 StandardScaler() 0 -> 0.48382519646474414
1566/3780 0.200 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.4937520610082207
1567/3780 0.200 4.703 1.0 StandardScaler() 0 -> 0.4918255639155249
1568/3780 0.200 4.703 1.0 MinMaxScaler() 0 -> 0.47930124873491115
1569/3780 0.200 5.968 scale StandardScaler() 0 -> 0.47891849033386275
1570/3780 0.200 5.968 scale MinMaxScaler() 0 -> 0.4793919564583995
1571/3780 0.200 5.968 auto StandardScaler() 0 -> 0.4789184903338623
1572/3780 0.200 5.968 auto MinMaxScaler() 0 -> 0.5103464115111319
1573/3780 0.200 5.968 0.01 StandardScaler() 0 -> 0.49341410733712165
1574/3780 0.200 5.968 0.01 MinMaxScaler() 0 -> 0.5524889758601557
1575/3780 0.200 5.968 0.03162277660168379 StandardScaler() 0 -> 0.4794986879915158
1576/3780 0.200 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5381537240731463
1577/3780 0.200 5.968 0.1 StandardScaler() 0 -> 0.47879103905692916
1578/3780 0.200 5.968 0.1 MinMaxScaler() 0 -> 0.5079934115762105
1579/3780 0.200 5.968 0.31622776601683794 StandardScaler() 0 -> 0.4906553131674192
1580/3780 0.200 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.49243907982573504
1581/3780 0.200 5.968 1.0 StandardScaler() 0 -> 0.4919507452713097
1582/3780 0.200 5.968 1.0 MinMaxScaler() 0 -> 0.4788324369596599
1583/3780 0.200 7.574 scale StandardScaler() 0 -> 0.4816218140866928
1584/3780 0.200 7.574 scale MinMaxScaler() 0 -> 0.48143524342775645
1585/3780 0.200 7.574 auto StandardScaler() 0 -> 0.4816218140866935
1586/3780 0.200 7.574 auto MinMaxScaler() 0 -> 0.5074632429148651
1587/3780 0.200 7.574 0.01 StandardScaler() 0 -> 0.4925109934068311
1588/3780 0.200 7.574 0.01 MinMaxScaler() 0 -> 0.5514766051071285
1589/3780 0.200 7.574 0.03162277660168379 StandardScaler() 0 -> 0.479651474834784
1590/3780 0.200 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5350512954461766
1591/3780 0.200 7.574 0.1 StandardScaler() 0 -> 0.4829814921973606
1592/3780 0.200 7.574 0.1 MinMaxScaler() 0 -> 0.5053276311548415
1593/3780 0.200 7.574 0.31622776601683794 StandardScaler() 0 -> 0.4980437479148497
1594/3780 0.200 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.4918361187553111
1595/3780 0.200 7.574 1.0 StandardScaler() 0 -> 0.49197620582402246
1596/3780 0.200 7.574 1.0 MinMaxScaler() 0 -> 0.4791054508726656
1597/3780 0.200 9.611 scale StandardScaler() 0 -> 0.486447400477311
1598/3780 0.200 9.611 scale MinMaxScaler() 0 -> 0.48350582299007394
1599/3780 0.200 9.611 auto StandardScaler() 0 -> 0.48644740047731266
1600/3780 0.200 9.611 auto MinMaxScaler() 0 -> 0.5050607309694977
1601/3780 0.200 9.611 0.01 StandardScaler() 0 -> 0.49151034422161577
1602/3780 0.200 9.611 0.01 MinMaxScaler() 0 -> 0.5507709898886933
1603/3780 0.200 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4801592118427511
1604/3780 0.200 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5318484116453188
1605/3780 0.200 9.611 0.1 StandardScaler() 0 -> 0.48939988926398215
1606/3780 0.200 9.611 0.1 MinMaxScaler() 0 -> 0.5029493542103737
1607/3780 0.200 9.611 0.31622776601683794 StandardScaler() 0 -> 0.5039505358217008
1608/3780 0.200 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4910237635352037
1609/3780 0.200 9.611 1.0 StandardScaler() 0 -> 0.49198378212432076
1610/3780 0.200 9.611 1.0 MinMaxScaler() 0 -> 0.4795931894732459
1611/3780 0.200 12.196 scale StandardScaler() 0 -> 0.49337295804347664
1612/3780 0.200 12.196 scale MinMaxScaler() 0 -> 0.48682236824858854
1613/3780 0.200 12.196 auto StandardScaler() 0 -> 0.493372958043476
1614/3780 0.200 12.196 auto MinMaxScaler() 0 -> 0.502674848567812
1615/3780 0.200 12.196 0.01 StandardScaler() 0 -> 0.4915715188861522
1616/3780 0.200 12.196 0.01 MinMaxScaler() 0 -> 0.5499732983266719
1617/3780 0.200 12.196 0.03162277660168379 StandardScaler() 0 -> 0.48083975488065717
1618/3780 0.200 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5284022053675163
1619/3780 0.200 12.196 0.1 StandardScaler() 0 -> 0.5002867810191375
1620/3780 0.200 12.196 0.1 MinMaxScaler() 0 -> 0.501579805829408
1621/3780 0.200 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5084278875760069
1622/3780 0.200 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4906517889478377
1623/3780 0.200 12.196 1.0 StandardScaler() 0 -> 0.49198140967204385
1624/3780 0.200 12.196 1.0 MinMaxScaler() 0 -> 0.4801058669880513
1625/3780 0.200 15.476 scale StandardScaler() 0 -> 0.5041817934338447
1626/3780 0.200 15.476 scale MinMaxScaler() 0 -> 0.49178799755574926
1627/3780 0.200 15.476 auto StandardScaler() 0 -> 0.5041817934338434
1628/3780 0.200 15.476 auto MinMaxScaler() 0 -> 0.5012713856535783
1629/3780 0.200 15.476 0.01 StandardScaler() 0 -> 0.4904967700410389
1630/3780 0.200 15.476 0.01 MinMaxScaler() 0 -> 0.5490545460973776
1631/3780 0.200 15.476 0.03162277660168379 StandardScaler() 0 -> 0.48110698678786173
1632/3780 0.200 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5250417918041042
1633/3780 0.200 15.476 0.1 StandardScaler() 0 -> 0.5162884306967306
1634/3780 0.200 15.476 0.1 MinMaxScaler() 0 -> 0.49992937534843257
1635/3780 0.200 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5115075891406833
1636/3780 0.200 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.48983451228062885
1637/3780 0.200 15.476 1.0 StandardScaler() 0 -> 0.49198140967204385
1638/3780 0.200 15.476 1.0 MinMaxScaler() 0 -> 0.48087010929560753
1639/3780 0.200 19.638 scale StandardScaler() 0 -> 0.5209201225855421
1640/3780 0.200 19.638 scale MinMaxScaler() 0 -> 0.4991451856078706
1641/3780 0.200 19.638 auto StandardScaler() 0 -> 0.5209201225855381
1642/3780 0.200 19.638 auto MinMaxScaler() 0 -> 0.4997541437738476
1643/3780 0.200 19.638 0.01 StandardScaler() 0 -> 0.49013322948235166
1644/3780 0.200 19.638 0.01 MinMaxScaler() 0 -> 0.5475906212101203
1645/3780 0.200 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4821002762447794
1646/3780 0.200 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5218333195752624
1647/3780 0.200 19.638 0.1 StandardScaler() 0 -> 0.5359570152035781
1648/3780 0.200 19.638 0.1 MinMaxScaler() 0 -> 0.49830544225461454
1649/3780 0.200 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5146908453411106
1650/3780 0.200 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.4895599323236288
1651/3780 0.200 19.638 1.0 StandardScaler() 0 -> 0.49198140967204385
1652/3780 0.200 19.638 1.0 MinMaxScaler() 0 -> 0.48172006769909875
1653/3780 0.200 24.920 scale StandardScaler() 0 -> 0.541311139125594
1654/3780 0.200 24.920 scale MinMaxScaler() 0 -> 0.5103285178849567
1655/3780 0.200 24.920 auto StandardScaler() 0 -> 0.541311139125597
1656/3780 0.200 24.920 auto MinMaxScaler() 0 -> 0.4983188659307447
1657/3780 0.200 24.920 0.01 StandardScaler() 0 -> 0.48946638361716777
1658/3780 0.200 24.920 0.01 MinMaxScaler() 0 -> 0.5461141116066196
1659/3780 0.200 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4836947696941896
1660/3780 0.200 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5188452996138285
1661/3780 0.200 24.920 0.1 StandardScaler() 0 -> 0.5574396846858621
1662/3780 0.200 24.920 0.1 MinMaxScaler() 0 -> 0.498258731026792
1663/3780 0.200 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5176894143956036
1664/3780 0.200 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.4884666712592103
1665/3780 0.200 24.920 1.0 StandardScaler() 0 -> 0.49198140967204385
1666/3780 0.200 24.920 1.0 MinMaxScaler() 0 -> 0.48360931705822807
1667/3780 0.200 31.623 scale StandardScaler() 0 -> 0.5643038312680864
1668/3780 0.200 31.623 scale MinMaxScaler() 0 -> 0.5251421862536044
1669/3780 0.200 31.623 auto StandardScaler() 0 -> 0.5643038312680785
1670/3780 0.200 31.623 auto MinMaxScaler() 0 -> 0.49844999182467226
1671/3780 0.200 31.623 0.01 StandardScaler() 0 -> 0.4887048670615896
1672/3780 0.200 31.623 0.01 MinMaxScaler() 0 -> 0.544276906772535
1673/3780 0.200 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4856190985555971
1674/3780 0.200 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5156931803369207
1675/3780 0.200 31.623 0.1 StandardScaler() 0 -> 0.5803625465747068
1676/3780 0.200 31.623 0.1 MinMaxScaler() 0 -> 0.49779892743557524
1677/3780 0.200 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5192438557417538
1678/3780 0.200 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4880067610750574
1679/3780 0.200 31.623 1.0 StandardScaler() 0 -> 0.49198140967204385
1680/3780 0.200 31.623 1.0 MinMaxScaler() 0 -> 0.48609871987488074
1681/3780 0.250 0.032 scale StandardScaler() 0 -> 0.5285852960741085
1682/3780 0.250 0.032 scale MinMaxScaler() 0 -> 0.5235075056756723
1683/3780 0.250 0.032 auto StandardScaler() 0 -> 0.5285852960741085
1684/3780 0.250 0.032 auto MinMaxScaler() 0 -> 0.632120758303752
1685/3780 0.250 0.032 0.01 StandardScaler() 0 -> 0.5823462042143855
1686/3780 0.250 0.032 0.01 MinMaxScaler() 0 -> 0.7561563462913933
1687/3780 0.250 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5383260142605478
1688/3780 0.250 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.707569672294268
1689/3780 0.250 0.032 0.1 StandardScaler() 0 -> 0.5302901216201005
1690/3780 0.250 0.032 0.1 MinMaxScaler() 0 -> 0.626697488638423
1691/3780 0.250 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6030631051893737
1692/3780 0.250 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5709238534984462
1693/3780 0.250 0.032 1.0 StandardScaler() 0 -> 0.7513953139732852
1694/3780 0.250 0.032 1.0 MinMaxScaler() 0 -> 0.5314772250008338
1695/3780 0.250 0.040 scale StandardScaler() 0 -> 0.5207726208131195
1696/3780 0.250 0.040 scale MinMaxScaler() 0 -> 0.51682874116449
1697/3780 0.250 0.040 auto StandardScaler() 0 -> 0.5207726208131195
1698/3780 0.250 0.040 auto MinMaxScaler() 0 -> 0.6183274762319703
1699/3780 0.250 0.040 0.01 StandardScaler() 0 -> 0.5726479960709879
1700/3780 0.250 0.040 0.01 MinMaxScaler() 0 -> 0.7494312768071629
1701/3780 0.250 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5313315155275606
1702/3780 0.250 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.6911045166308217
1703/3780 0.250 0.040 0.1 StandardScaler() 0 -> 0.5217150216337495
1704/3780 0.250 0.040 0.1 MinMaxScaler() 0 -> 0.613772722517353
1705/3780 0.250 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5860145742632042
1706/3780 0.250 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5612985205326231
1707/3780 0.250 0.040 1.0 StandardScaler() 0 -> 0.7435134430901901
1708/3780 0.250 0.040 1.0 MinMaxScaler() 0 -> 0.5254475105371266
1709/3780 0.250 0.051 scale StandardScaler() 0 -> 0.5143041044315896
1710/3780 0.250 0.051 scale MinMaxScaler() 0 -> 0.5115124608810201
1711/3780 0.250 0.051 auto StandardScaler() 0 -> 0.5143041044315896
1712/3780 0.250 0.051 auto MinMaxScaler() 0 -> 0.6063808458274978
1713/3780 0.250 0.051 0.01 StandardScaler() 0 -> 0.5625763665303544
1714/3780 0.250 0.051 0.01 MinMaxScaler() 0 -> 0.7411362691315895
1715/3780 0.250 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5247777733763822
1716/3780 0.250 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6724338395063447
1717/3780 0.250 0.051 0.1 StandardScaler() 0 -> 0.5152008395402433
1718/3780 0.250 0.051 0.1 MinMaxScaler() 0 -> 0.601167897793961
1719/3780 0.250 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5699758277241757
1720/3780 0.250 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5529737834571185
1721/3780 0.250 0.051 1.0 StandardScaler() 0 -> 0.733822953255136
1722/3780 0.250 0.051 1.0 MinMaxScaler() 0 -> 0.5199975518096963
1723/3780 0.250 0.065 scale StandardScaler() 0 -> 0.5081787647490982
1724/3780 0.250 0.065 scale MinMaxScaler() 0 -> 0.5066885765816443
1725/3780 0.250 0.065 auto StandardScaler() 0 -> 0.5081787647490982
1726/3780 0.250 0.065 auto MinMaxScaler() 0 -> 0.5931594178843156
1727/3780 0.250 0.065 0.01 StandardScaler() 0 -> 0.5546433280200271
1728/3780 0.250 0.065 0.01 MinMaxScaler() 0 -> 0.7309260453640203
1729/3780 0.250 0.065 0.03162277660168379 StandardScaler() 0 -> 0.519111417274721
1730/3780 0.250 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6528992097648694
1731/3780 0.250 0.065 0.1 StandardScaler() 0 -> 0.5086703276136127
1732/3780 0.250 0.065 0.1 MinMaxScaler() 0 -> 0.589114346599685
1733/3780 0.250 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5564424694143045
1734/3780 0.250 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5455091122293246
1735/3780 0.250 0.065 1.0 StandardScaler() 0 -> 0.7220283116705498
1736/3780 0.250 0.065 1.0 MinMaxScaler() 0 -> 0.5155752160199663
1737/3780 0.250 0.082 scale StandardScaler() 0 -> 0.5024150393292469
1738/3780 0.250 0.082 scale MinMaxScaler() 0 -> 0.5023056901022536
1739/3780 0.250 0.082 auto StandardScaler() 0 -> 0.5024150393292469
1740/3780 0.250 0.082 auto MinMaxScaler() 0 -> 0.581860290670109
1741/3780 0.250 0.082 0.01 StandardScaler() 0 -> 0.5466119533914543
1742/3780 0.250 0.082 0.01 MinMaxScaler() 0 -> 0.718626790485712
1743/3780 0.250 0.082 0.03162277660168379 StandardScaler() 0 -> 0.513884131842647
1744/3780 0.250 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.636139656021437
1745/3780 0.250 0.082 0.1 StandardScaler() 0 -> 0.503210231903764
1746/3780 0.250 0.082 0.1 MinMaxScaler() 0 -> 0.5777623760619801
1747/3780 0.250 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5430851285624958
1748/3780 0.250 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5404460085682979
1749/3780 0.250 0.082 1.0 StandardScaler() 0 -> 0.7079799495676494
1750/3780 0.250 0.082 1.0 MinMaxScaler() 0 -> 0.5109240430247267
1751/3780 0.250 0.104 scale StandardScaler() 0 -> 0.4973529404117389
1752/3780 0.250 0.104 scale MinMaxScaler() 0 -> 0.49759435039173927
1753/3780 0.250 0.104 auto StandardScaler() 0 -> 0.4973529404117389
1754/3780 0.250 0.104 auto MinMaxScaler() 0 -> 0.5728231911445666
1755/3780 0.250 0.104 0.01 StandardScaler() 0 -> 0.5409403359218936
1756/3780 0.250 0.104 0.01 MinMaxScaler() 0 -> 0.703995175224438
1757/3780 0.250 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5089938211984227
1758/3780 0.250 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6223454817432735
1759/3780 0.250 0.104 0.1 StandardScaler() 0 -> 0.49747096382774925
1760/3780 0.250 0.104 0.1 MinMaxScaler() 0 -> 0.5690156726398916
1761/3780 0.250 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5307154820755579
1762/3780 0.250 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5360863279896888
1763/3780 0.250 0.104 1.0 StandardScaler() 0 -> 0.6915113188388653
1764/3780 0.250 0.104 1.0 MinMaxScaler() 0 -> 0.5070367972840165
1765/3780 0.250 0.132 scale StandardScaler() 0 -> 0.4922824626999677
1766/3780 0.250 0.132 scale MinMaxScaler() 0 -> 0.4936249562153052
1767/3780 0.250 0.132 auto StandardScaler() 0 -> 0.49228246269996756
1768/3780 0.250 0.132 auto MinMaxScaler() 0 -> 0.5647551438184865
1769/3780 0.250 0.132 0.01 StandardScaler() 0 -> 0.5363302767701683
1770/3780 0.250 0.132 0.01 MinMaxScaler() 0 -> 0.6869870290572351
1771/3780 0.250 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5046148834004961
1772/3780 0.250 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6106844367756158
1773/3780 0.250 0.132 0.1 StandardScaler() 0 -> 0.4923560347416127
1774/3780 0.250 0.132 0.1 MinMaxScaler() 0 -> 0.5617509796971228
1775/3780 0.250 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5186402072971289
1776/3780 0.250 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5314671304634414
1777/3780 0.250 0.132 1.0 StandardScaler() 0 -> 0.6726859489237965
1778/3780 0.250 0.132 1.0 MinMaxScaler() 0 -> 0.5033966056313991
1779/3780 0.250 0.168 scale StandardScaler() 0 -> 0.48810758601984894
1780/3780 0.250 0.168 scale MinMaxScaler() 0 -> 0.48970144447623815
1781/3780 0.250 0.168 auto StandardScaler() 0 -> 0.488107586019849
1782/3780 0.250 0.168 auto MinMaxScaler() 0 -> 0.558999483116792
1783/3780 0.250 0.168 0.01 StandardScaler() 0 -> 0.5318841653116722
1784/3780 0.250 0.168 0.01 MinMaxScaler() 0 -> 0.6680816151848421
1785/3780 0.250 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5008105245382035
1786/3780 0.250 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.5973709352102353
1787/3780 0.250 0.168 0.1 StandardScaler() 0 -> 0.48791262497865745
1788/3780 0.250 0.168 0.1 MinMaxScaler() 0 -> 0.556248635205569
1789/3780 0.250 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5083541857036581
1790/3780 0.250 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5272442703557824
1791/3780 0.250 0.168 1.0 StandardScaler() 0 -> 0.6519520669151443
1792/3780 0.250 0.168 1.0 MinMaxScaler() 0 -> 0.4998527456284973
1793/3780 0.250 0.213 scale StandardScaler() 0 -> 0.48518634731298577
1794/3780 0.250 0.213 scale MinMaxScaler() 0 -> 0.4866818470499957
1795/3780 0.250 0.213 auto StandardScaler() 0 -> 0.4851863473129858
1796/3780 0.250 0.213 auto MinMaxScaler() 0 -> 0.5536469005230967
1797/3780 0.250 0.213 0.01 StandardScaler() 0 -> 0.5274878907055598
1798/3780 0.250 0.213 0.01 MinMaxScaler() 0 -> 0.6488685907903226
1799/3780 0.250 0.213 0.03162277660168379 StandardScaler() 0 -> 0.497966043379601
1800/3780 0.250 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5863395537332997
1801/3780 0.250 0.213 0.1 StandardScaler() 0 -> 0.48475338954120256
1802/3780 0.250 0.213 0.1 MinMaxScaler() 0 -> 0.5512878853327511
1803/3780 0.250 0.213 0.31622776601683794 StandardScaler() 0 -> 0.4987961470620945
1804/3780 0.250 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5234631428090176
1805/3780 0.250 0.213 1.0 StandardScaler() 0 -> 0.6291004441708085
1806/3780 0.250 0.213 1.0 MinMaxScaler() 0 -> 0.4968435916395364
1807/3780 0.250 0.270 scale StandardScaler() 0 -> 0.4827099277388891
1808/3780 0.250 0.270 scale MinMaxScaler() 0 -> 0.48445720547051935
1809/3780 0.250 0.270 auto StandardScaler() 0 -> 0.4827099277388891
1810/3780 0.250 0.270 auto MinMaxScaler() 0 -> 0.5500954210867063
1811/3780 0.250 0.270 0.01 StandardScaler() 0 -> 0.5221810518067495
1812/3780 0.250 0.270 0.01 MinMaxScaler() 0 -> 0.6331405183801787
1813/3780 0.250 0.270 0.03162277660168379 StandardScaler() 0 -> 0.4956479876713333
1814/3780 0.250 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.576548379798337
1815/3780 0.250 0.270 0.1 StandardScaler() 0 -> 0.482065728723929
1816/3780 0.250 0.270 0.1 MinMaxScaler() 0 -> 0.5483451983413166
1817/3780 0.250 0.270 0.31622776601683794 StandardScaler() 0 -> 0.48999846384639484
1818/3780 0.250 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5197585920400695
1819/3780 0.250 0.270 1.0 StandardScaler() 0 -> 0.6049355724695094
1820/3780 0.250 0.270 1.0 MinMaxScaler() 0 -> 0.4944085103560231
1821/3780 0.250 0.342 scale StandardScaler() 0 -> 0.4806280347557917
1822/3780 0.250 0.342 scale MinMaxScaler() 0 -> 0.482467976237915
1823/3780 0.250 0.342 auto StandardScaler() 0 -> 0.48062803475579186
1824/3780 0.250 0.342 auto MinMaxScaler() 0 -> 0.5474503313718784
1825/3780 0.250 0.342 0.01 StandardScaler() 0 -> 0.5184177393943784
1826/3780 0.250 0.342 0.01 MinMaxScaler() 0 -> 0.6195447564768176
1827/3780 0.250 0.342 0.03162277660168379 StandardScaler() 0 -> 0.49291696022095716
1828/3780 0.250 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5691315439966781
1829/3780 0.250 0.342 0.1 StandardScaler() 0 -> 0.4799403727503164
1830/3780 0.250 0.342 0.1 MinMaxScaler() 0 -> 0.5455867897894006
1831/3780 0.250 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4826329119460158
1832/3780 0.250 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5162104170118224
1833/3780 0.250 0.342 1.0 StandardScaler() 0 -> 0.5812245845069467
1834/3780 0.250 0.342 1.0 MinMaxScaler() 0 -> 0.4923048214060381
1835/3780 0.250 0.434 scale StandardScaler() 0 -> 0.47824773185000574
1836/3780 0.250 0.434 scale MinMaxScaler() 0 -> 0.47992883522659663
1837/3780 0.250 0.434 auto StandardScaler() 0 -> 0.4782477318500058
1838/3780 0.250 0.434 auto MinMaxScaler() 0 -> 0.5445468429638094
1839/3780 0.250 0.434 0.01 StandardScaler() 0 -> 0.5153128948126471
1840/3780 0.250 0.434 0.01 MinMaxScaler() 0 -> 0.6078203343027545
1841/3780 0.250 0.434 0.03162277660168379 StandardScaler() 0 -> 0.4914610332195601
1842/3780 0.250 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5632434396029135
1843/3780 0.250 0.434 0.1 StandardScaler() 0 -> 0.47755045552948716
1844/3780 0.250 0.434 0.1 MinMaxScaler() 0 -> 0.5427900851792693
1845/3780 0.250 0.434 0.31622776601683794 StandardScaler() 0 -> 0.4765819470928719
1846/3780 0.250 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5132790241374116
1847/3780 0.250 0.434 1.0 StandardScaler() 0 -> 0.5590298853620815
1848/3780 0.250 0.434 1.0 MinMaxScaler() 0 -> 0.4904677359471543
1849/3780 0.250 0.551 scale StandardScaler() 0 -> 0.47637459873926913
1850/3780 0.250 0.551 scale MinMaxScaler() 0 -> 0.477173860615522
1851/3780 0.250 0.551 auto StandardScaler() 0 -> 0.4763745987392692
1852/3780 0.250 0.551 auto MinMaxScaler() 0 -> 0.5422473620567266
1853/3780 0.250 0.551 0.01 StandardScaler() 0 -> 0.511760537017062
1854/3780 0.250 0.551 0.01 MinMaxScaler() 0 -> 0.5950177249912514
1855/3780 0.250 0.551 0.03162277660168379 StandardScaler() 0 -> 0.48906854170778197
1856/3780 0.250 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5583667260105135
1857/3780 0.250 0.551 0.1 StandardScaler() 0 -> 0.47593705895367466
1858/3780 0.250 0.551 0.1 MinMaxScaler() 0 -> 0.5400123906494735
1859/3780 0.250 0.551 0.31622776601683794 StandardScaler() 0 -> 0.47137822430190496
1860/3780 0.250 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5096883495765807
1861/3780 0.250 0.551 1.0 StandardScaler() 0 -> 0.5371834290155556
1862/3780 0.250 0.551 1.0 MinMaxScaler() 0 -> 0.48833426832490323
1863/3780 0.250 0.700 scale StandardScaler() 0 -> 0.4752064913213565
1864/3780 0.250 0.700 scale MinMaxScaler() 0 -> 0.4747214170792602
1865/3780 0.250 0.700 auto StandardScaler() 0 -> 0.47520649132135634
1866/3780 0.250 0.700 auto MinMaxScaler() 0 -> 0.5394126668403875
1867/3780 0.250 0.700 0.01 StandardScaler() 0 -> 0.5087915424249146
1868/3780 0.250 0.700 0.01 MinMaxScaler() 0 -> 0.5841756939064466
1869/3780 0.250 0.700 0.03162277660168379 StandardScaler() 0 -> 0.486817555722034
1870/3780 0.250 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5550029868418646
1871/3780 0.250 0.700 0.1 StandardScaler() 0 -> 0.4743800143060832
1872/3780 0.250 0.700 0.1 MinMaxScaler() 0 -> 0.5368742096677978
1873/3780 0.250 0.700 0.31622776601683794 StandardScaler() 0 -> 0.46757233885497484
1874/3780 0.250 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5066701599506716
1875/3780 0.250 0.700 1.0 StandardScaler() 0 -> 0.5186410847224717
1876/3780 0.250 0.700 1.0 MinMaxScaler() 0 -> 0.48631612897371407
1877/3780 0.250 0.888 scale StandardScaler() 0 -> 0.47416342401585004
1878/3780 0.250 0.888 scale MinMaxScaler() 0 -> 0.4733628264166672
1879/3780 0.250 0.888 auto StandardScaler() 0 -> 0.47416342401585015
1880/3780 0.250 0.888 auto MinMaxScaler() 0 -> 0.5362564252972875
1881/3780 0.250 0.888 0.01 StandardScaler() 0 -> 0.5054415315214488
1882/3780 0.250 0.888 0.01 MinMaxScaler() 0 -> 0.575983934600926
1883/3780 0.250 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4853518095507679
1884/3780 0.250 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5533070803049316
1885/3780 0.250 0.888 0.1 StandardScaler() 0 -> 0.47225620624795656
1886/3780 0.250 0.888 0.1 MinMaxScaler() 0 -> 0.5337344940888825
1887/3780 0.250 0.888 0.31622776601683794 StandardScaler() 0 -> 0.46504117294754516
1888/3780 0.250 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5036211673267047
1889/3780 0.250 0.888 1.0 StandardScaler() 0 -> 0.5077659947257833
1890/3780 0.250 0.888 1.0 MinMaxScaler() 0 -> 0.4849703949299249
1891/3780 0.250 1.126 scale StandardScaler() 0 -> 0.4720434685616495
1892/3780 0.250 1.126 scale MinMaxScaler() 0 -> 0.4727416553531945
1893/3780 0.250 1.126 auto StandardScaler() 0 -> 0.4720434685616495
1894/3780 0.250 1.126 auto MinMaxScaler() 0 -> 0.5332435656030085
1895/3780 0.250 1.126 0.01 StandardScaler() 0 -> 0.5023379674512096
1896/3780 0.250 1.126 0.01 MinMaxScaler() 0 -> 0.5685680292157543
1897/3780 0.250 1.126 0.03162277660168379 StandardScaler() 0 -> 0.4844577115538488
1898/3780 0.250 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5516264096533737
1899/3780 0.250 1.126 0.1 StandardScaler() 0 -> 0.4705455404071599
1900/3780 0.250 1.126 0.1 MinMaxScaler() 0 -> 0.5308465353660403
1901/3780 0.250 1.126 0.31622776601683794 StandardScaler() 0 -> 0.46400899687570085
1902/3780 0.250 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5015381917959884
1903/3780 0.250 1.126 1.0 StandardScaler() 0 -> 0.5025910537535976
1904/3780 0.250 1.126 1.0 MinMaxScaler() 0 -> 0.4838818388891943
1905/3780 0.250 1.429 scale StandardScaler() 0 -> 0.47111821782560176
1906/3780 0.250 1.429 scale MinMaxScaler() 0 -> 0.47227070251633935
1907/3780 0.250 1.429 auto StandardScaler() 0 -> 0.47111821782560126
1908/3780 0.250 1.429 auto MinMaxScaler() 0 -> 0.5301777924845416
1909/3780 0.250 1.429 0.01 StandardScaler() 0 -> 0.5002169029772477
1910/3780 0.250 1.429 0.01 MinMaxScaler() 0 -> 0.5630028484149653
1911/3780 0.250 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48387540906671456
1912/3780 0.250 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5501612771504601
1913/3780 0.250 1.429 0.1 StandardScaler() 0 -> 0.47001964550940367
1914/3780 0.250 1.429 0.1 MinMaxScaler() 0 -> 0.5279636376815268
1915/3780 0.250 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4635654466182942
1916/3780 0.250 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.4989477865842251
1917/3780 0.250 1.429 1.0 StandardScaler() 0 -> 0.4985813081024315
1918/3780 0.250 1.429 1.0 MinMaxScaler() 0 -> 0.48243560557680754
1919/3780 0.250 1.814 scale StandardScaler() 0 -> 0.4708124845530135
1920/3780 0.250 1.814 scale MinMaxScaler() 0 -> 0.47229255906733064
1921/3780 0.250 1.814 auto StandardScaler() 0 -> 0.47081248455301344
1922/3780 0.250 1.814 auto MinMaxScaler() 0 -> 0.527442623293683
1923/3780 0.250 1.814 0.01 StandardScaler() 0 -> 0.49835090451549596
1924/3780 0.250 1.814 0.01 MinMaxScaler() 0 -> 0.5590252099670526
1925/3780 0.250 1.814 0.03162277660168379 StandardScaler() 0 -> 0.4825970818379044
1926/3780 0.250 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5484345539305088
1927/3780 0.250 1.814 0.1 StandardScaler() 0 -> 0.4696638564160624
1928/3780 0.250 1.814 0.1 MinMaxScaler() 0 -> 0.5245896533972175
1929/3780 0.250 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4650952622276381
1930/3780 0.250 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.4972322657594492
1931/3780 0.250 1.814 1.0 StandardScaler() 0 -> 0.4967144883912608
1932/3780 0.250 1.814 1.0 MinMaxScaler() 0 -> 0.48117317658003494
1933/3780 0.250 2.302 scale StandardScaler() 0 -> 0.47045739324501074
1934/3780 0.250 2.302 scale MinMaxScaler() 0 -> 0.47272537890769023
1935/3780 0.250 2.302 auto StandardScaler() 0 -> 0.47045739324501074
1936/3780 0.250 2.302 auto MinMaxScaler() 0 -> 0.5239345844016627
1937/3780 0.250 2.302 0.01 StandardScaler() 0 -> 0.49689266329264486
1938/3780 0.250 2.302 0.01 MinMaxScaler() 0 -> 0.5564520783400042
1939/3780 0.250 2.302 0.03162277660168379 StandardScaler() 0 -> 0.481463209295742
1940/3780 0.250 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5468103601832182
1941/3780 0.250 2.302 0.1 StandardScaler() 0 -> 0.46994858053827976
1942/3780 0.250 2.302 0.1 MinMaxScaler() 0 -> 0.5214154294596992
1943/3780 0.250 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4689837492723834
1944/3780 0.250 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.496157317282401
1945/3780 0.250 2.302 1.0 StandardScaler() 0 -> 0.49638537863718585
1946/3780 0.250 2.302 1.0 MinMaxScaler() 0 -> 0.47986206129306136
1947/3780 0.250 2.921 scale StandardScaler() 0 -> 0.4709994780733932
1948/3780 0.250 2.921 scale MinMaxScaler() 0 -> 0.47293434196373757
1949/3780 0.250 2.921 auto StandardScaler() 0 -> 0.47099947807339415
1950/3780 0.250 2.921 auto MinMaxScaler() 0 -> 0.5206892583949312
1951/3780 0.250 2.921 0.01 StandardScaler() 0 -> 0.49529153587351443
1952/3780 0.250 2.921 0.01 MinMaxScaler() 0 -> 0.555124744462042
1953/3780 0.250 2.921 0.03162277660168379 StandardScaler() 0 -> 0.4805461008009299
1954/3780 0.250 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5448353298511917
1955/3780 0.250 2.921 0.1 StandardScaler() 0 -> 0.47039783206291946
1956/3780 0.250 2.921 0.1 MinMaxScaler() 0 -> 0.5183639793434919
1957/3780 0.250 2.921 0.31622776601683794 StandardScaler() 0 -> 0.47256864355341577
1958/3780 0.250 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49482791316995867
1959/3780 0.250 2.921 1.0 StandardScaler() 0 -> 0.49619804642319804
1960/3780 0.250 2.921 1.0 MinMaxScaler() 0 -> 0.47865456005096124
1961/3780 0.250 3.707 scale StandardScaler() 0 -> 0.47178777202366745
1962/3780 0.250 3.707 scale MinMaxScaler() 0 -> 0.4729584572288963
1963/3780 0.250 3.707 auto StandardScaler() 0 -> 0.4717877720236676
1964/3780 0.250 3.707 auto MinMaxScaler() 0 -> 0.517611822856471
1965/3780 0.250 3.707 0.01 StandardScaler() 0 -> 0.49456438419372883
1966/3780 0.250 3.707 0.01 MinMaxScaler() 0 -> 0.55369702229866
1967/3780 0.250 3.707 0.03162277660168379 StandardScaler() 0 -> 0.48023006990057765
1968/3780 0.250 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5431659877588685
1969/3780 0.250 3.707 0.1 StandardScaler() 0 -> 0.47140030850913367
1970/3780 0.250 3.707 0.1 MinMaxScaler() 0 -> 0.51460735488529
1971/3780 0.250 3.707 0.31622776601683794 StandardScaler() 0 -> 0.4770654943536672
1972/3780 0.250 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.49386051524034075
1973/3780 0.250 3.707 1.0 StandardScaler() 0 -> 0.49624662056915597
1974/3780 0.250 3.707 1.0 MinMaxScaler() 0 -> 0.47794867469717534
1975/3780 0.250 4.703 scale StandardScaler() 0 -> 0.47325138793346033
1976/3780 0.250 4.703 scale MinMaxScaler() 0 -> 0.47486430783170297
1977/3780 0.250 4.703 auto StandardScaler() 0 -> 0.4732513879334612
1978/3780 0.250 4.703 auto MinMaxScaler() 0 -> 0.514069304506506
1979/3780 0.250 4.703 0.01 StandardScaler() 0 -> 0.4931019238190289
1980/3780 0.250 4.703 0.01 MinMaxScaler() 0 -> 0.5529329044732303
1981/3780 0.250 4.703 0.03162277660168379 StandardScaler() 0 -> 0.47975335817321135
1982/3780 0.250 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5407951550636939
1983/3780 0.250 4.703 0.1 StandardScaler() 0 -> 0.47392953923380904
1984/3780 0.250 4.703 0.1 MinMaxScaler() 0 -> 0.5118367093293084
1985/3780 0.250 4.703 0.31622776601683794 StandardScaler() 0 -> 0.4819173801329452
1986/3780 0.250 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.4929275949566894
1987/3780 0.250 4.703 1.0 StandardScaler() 0 -> 0.4963062318738006
1988/3780 0.250 4.703 1.0 MinMaxScaler() 0 -> 0.4779695964180493
1989/3780 0.250 5.968 scale StandardScaler() 0 -> 0.47591681918281176
1990/3780 0.250 5.968 scale MinMaxScaler() 0 -> 0.47705668357185943
1991/3780 0.250 5.968 auto StandardScaler() 0 -> 0.47591681918281203
1992/3780 0.250 5.968 auto MinMaxScaler() 0 -> 0.51120786083092
1993/3780 0.250 5.968 0.01 StandardScaler() 0 -> 0.4923888331573904
1994/3780 0.250 5.968 0.01 MinMaxScaler() 0 -> 0.5520033929591724
1995/3780 0.250 5.968 0.03162277660168379 StandardScaler() 0 -> 0.47901008066068745
1996/3780 0.250 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5383074594359784
1997/3780 0.250 5.968 0.1 StandardScaler() 0 -> 0.4766289389516845
1998/3780 0.250 5.968 0.1 MinMaxScaler() 0 -> 0.5084168795137295
1999/3780 0.250 5.968 0.31622776601683794 StandardScaler() 0 -> 0.4886389839358352
2000/3780 0.250 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.4918310516902708
2001/3780 0.250 5.968 1.0 StandardScaler() 0 -> 0.4963300894266975
2002/3780 0.250 5.968 1.0 MinMaxScaler() 0 -> 0.4771597124465788
2003/3780 0.250 7.574 scale StandardScaler() 0 -> 0.4789968200828629
2004/3780 0.250 7.574 scale MinMaxScaler() 0 -> 0.47880522981641693
2005/3780 0.250 7.574 auto StandardScaler() 0 -> 0.47899682008286276
2006/3780 0.250 7.574 auto MinMaxScaler() 0 -> 0.5079982579788548
2007/3780 0.250 7.574 0.01 StandardScaler() 0 -> 0.4918447778699715
2008/3780 0.250 7.574 0.01 MinMaxScaler() 0 -> 0.5513626711852856
2009/3780 0.250 7.574 0.03162277660168379 StandardScaler() 0 -> 0.4781812681911301
2010/3780 0.250 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5354546367729957
2011/3780 0.250 7.574 0.1 StandardScaler() 0 -> 0.481144382530998
2012/3780 0.250 7.574 0.1 MinMaxScaler() 0 -> 0.5057708471883966
2013/3780 0.250 7.574 0.31622776601683794 StandardScaler() 0 -> 0.4941428773625877
2014/3780 0.250 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.4915448175193518
2015/3780 0.250 7.574 1.0 StandardScaler() 0 -> 0.4963359096227918
2016/3780 0.250 7.574 1.0 MinMaxScaler() 0 -> 0.4770249919211455
2017/3780 0.250 9.611 scale StandardScaler() 0 -> 0.48411878727801616
2018/3780 0.250 9.611 scale MinMaxScaler() 0 -> 0.48157854347381096
2019/3780 0.250 9.611 auto StandardScaler() 0 -> 0.4841187872780182
2020/3780 0.250 9.611 auto MinMaxScaler() 0 -> 0.505396773512173
2021/3780 0.250 9.611 0.01 StandardScaler() 0 -> 0.49128579245023296
2022/3780 0.250 9.611 0.01 MinMaxScaler() 0 -> 0.5503703404530208
2023/3780 0.250 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4786554739284891
2024/3780 0.250 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5326833140907236
2025/3780 0.250 9.611 0.1 StandardScaler() 0 -> 0.4876238651032539
2026/3780 0.250 9.611 0.1 MinMaxScaler() 0 -> 0.5035361025836298
2027/3780 0.250 9.611 0.31622776601683794 StandardScaler() 0 -> 0.4991760283044573
2028/3780 0.250 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.49047928013195824
2029/3780 0.250 9.611 1.0 StandardScaler() 0 -> 0.496335060606013
2030/3780 0.250 9.611 1.0 MinMaxScaler() 0 -> 0.4773332392168865
2031/3780 0.250 12.196 scale StandardScaler() 0 -> 0.4908963783251757
2032/3780 0.250 12.196 scale MinMaxScaler() 0 -> 0.48532264282751253
2033/3780 0.250 12.196 auto StandardScaler() 0 -> 0.49089637832518
2034/3780 0.250 12.196 auto MinMaxScaler() 0 -> 0.5031931048549644
2035/3780 0.250 12.196 0.01 StandardScaler() 0 -> 0.490676831718887
2036/3780 0.250 12.196 0.01 MinMaxScaler() 0 -> 0.5493033688544985
2037/3780 0.250 12.196 0.03162277660168379 StandardScaler() 0 -> 0.47926722928700766
2038/3780 0.250 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5297145860218663
2039/3780 0.250 12.196 0.1 StandardScaler() 0 -> 0.4977625886861399
2040/3780 0.250 12.196 0.1 MinMaxScaler() 0 -> 0.5014851941176849
2041/3780 0.250 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5027498199160906
2042/3780 0.250 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4892181413328435
2043/3780 0.250 12.196 1.0 StandardScaler() 0 -> 0.4963366059446143
2044/3780 0.250 12.196 1.0 MinMaxScaler() 0 -> 0.4776543402134332
2045/3780 0.250 15.476 scale StandardScaler() 0 -> 0.5010744211295538
2046/3780 0.250 15.476 scale MinMaxScaler() 0 -> 0.48980583490509794
2047/3780 0.250 15.476 auto StandardScaler() 0 -> 0.5010744211295571
2048/3780 0.250 15.476 auto MinMaxScaler() 0 -> 0.5013594398989412
2049/3780 0.250 15.476 0.01 StandardScaler() 0 -> 0.48960088302342103
2050/3780 0.250 15.476 0.01 MinMaxScaler() 0 -> 0.5485482609357152
2051/3780 0.250 15.476 0.03162277660168379 StandardScaler() 0 -> 0.479883936195964
2052/3780 0.250 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5264896074692101
2053/3780 0.250 15.476 0.1 StandardScaler() 0 -> 0.5129663612770471
2054/3780 0.250 15.476 0.1 MinMaxScaler() 0 -> 0.5000792816524379
2055/3780 0.250 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5054369829533941
2056/3780 0.250 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.48819961270296597
2057/3780 0.250 15.476 1.0 StandardScaler() 0 -> 0.4963366059446143
2058/3780 0.250 15.476 1.0 MinMaxScaler() 0 -> 0.4785934093977966
2059/3780 0.250 19.638 scale StandardScaler() 0 -> 0.5178356983806411
2060/3780 0.250 19.638 scale MinMaxScaler() 0 -> 0.49718660220102145
2061/3780 0.250 19.638 auto StandardScaler() 0 -> 0.5178356983806428
2062/3780 0.250 19.638 auto MinMaxScaler() 0 -> 0.4999247282295187
2063/3780 0.250 19.638 0.01 StandardScaler() 0 -> 0.48892012345939784
2064/3780 0.250 19.638 0.01 MinMaxScaler() 0 -> 0.5473140623770402
2065/3780 0.250 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4807278311837921
2066/3780 0.250 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.523244115603101
2067/3780 0.250 19.638 0.1 StandardScaler() 0 -> 0.530795191823495
2068/3780 0.250 19.638 0.1 MinMaxScaler() 0 -> 0.49876813980410456
2069/3780 0.250 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5082087921211152
2070/3780 0.250 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.48737085640275213
2071/3780 0.250 19.638 1.0 StandardScaler() 0 -> 0.4963366059446143
2072/3780 0.250 19.638 1.0 MinMaxScaler() 0 -> 0.4790391847164506
2073/3780 0.250 24.920 scale StandardScaler() 0 -> 0.5363098291070574
2074/3780 0.250 24.920 scale MinMaxScaler() 0 -> 0.508148844511907
2075/3780 0.250 24.920 auto StandardScaler() 0 -> 0.5363098291070604
2076/3780 0.250 24.920 auto MinMaxScaler() 0 -> 0.4987078991895591
2077/3780 0.250 24.920 0.01 StandardScaler() 0 -> 0.4877044943121945
2078/3780 0.250 24.920 0.01 MinMaxScaler() 0 -> 0.5461178357066849
2079/3780 0.250 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4820964779136471
2080/3780 0.250 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5202797841807136
2081/3780 0.250 24.920 0.1 StandardScaler() 0 -> 0.5497236683308434
2082/3780 0.250 24.920 0.1 MinMaxScaler() 0 -> 0.4981322907399403
2083/3780 0.250 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5101755207986259
2084/3780 0.250 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.4863561064943765
2085/3780 0.250 24.920 1.0 StandardScaler() 0 -> 0.4963366059446143
2086/3780 0.250 24.920 1.0 MinMaxScaler() 0 -> 0.48066689378684196
2087/3780 0.250 31.623 scale StandardScaler() 0 -> 0.557008434328964
2088/3780 0.250 31.623 scale MinMaxScaler() 0 -> 0.5208442573839079
2089/3780 0.250 31.623 auto StandardScaler() 0 -> 0.5570084343289697
2090/3780 0.250 31.623 auto MinMaxScaler() 0 -> 0.49821595089713294
2091/3780 0.250 31.623 0.01 StandardScaler() 0 -> 0.4878412391997227
2092/3780 0.250 31.623 0.01 MinMaxScaler() 0 -> 0.5443536721473826
2093/3780 0.250 31.623 0.03162277660168379 StandardScaler() 0 -> 0.48468151340001114
2094/3780 0.250 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5169642768418242
2095/3780 0.250 31.623 0.1 StandardScaler() 0 -> 0.5695772633169881
2096/3780 0.250 31.623 0.1 MinMaxScaler() 0 -> 0.49729698999449634
2097/3780 0.250 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5112599468693579
2098/3780 0.250 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4855788743076323
2099/3780 0.250 31.623 1.0 StandardScaler() 0 -> 0.4963366059446143
2100/3780 0.250 31.623 1.0 MinMaxScaler() 0 -> 0.484844119318363
2101/3780 0.300 0.032 scale StandardScaler() 0 -> 0.5309106855175726
2102/3780 0.300 0.032 scale MinMaxScaler() 0 -> 0.5267412555923943
2103/3780 0.300 0.032 auto StandardScaler() 0 -> 0.5309106855175726
2104/3780 0.300 0.032 auto MinMaxScaler() 0 -> 0.630900169897446
2105/3780 0.300 0.032 0.01 StandardScaler() 0 -> 0.5801489439779756
2106/3780 0.300 0.032 0.01 MinMaxScaler() 0 -> 0.7729141550465775
2107/3780 0.300 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5413414477677444
2108/3780 0.300 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7200497951104273
2109/3780 0.300 0.032 0.1 StandardScaler() 0 -> 0.5322146869059509
2110/3780 0.300 0.032 0.1 MinMaxScaler() 0 -> 0.6240757534459144
2111/3780 0.300 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6065071347190399
2112/3780 0.300 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5691131551482673
2113/3780 0.300 0.032 1.0 StandardScaler() 0 -> 0.7704640649091209
2114/3780 0.300 0.032 1.0 MinMaxScaler() 0 -> 0.5341249621327414
2115/3780 0.300 0.040 scale StandardScaler() 0 -> 0.5240849309563801
2116/3780 0.300 0.040 scale MinMaxScaler() 0 -> 0.5207872839256115
2117/3780 0.300 0.040 auto StandardScaler() 0 -> 0.5240849309563801
2118/3780 0.300 0.040 auto MinMaxScaler() 0 -> 0.6145833749250671
2119/3780 0.300 0.040 0.01 StandardScaler() 0 -> 0.5700939330117736
2120/3780 0.300 0.040 0.01 MinMaxScaler() 0 -> 0.765642316895543
2121/3780 0.300 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5333223137309296
2122/3780 0.300 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7018222269140314
2123/3780 0.300 0.040 0.1 StandardScaler() 0 -> 0.5254978271340672
2124/3780 0.300 0.040 0.1 MinMaxScaler() 0 -> 0.6093323477199775
2125/3780 0.300 0.040 0.31622776601683794 StandardScaler() 0 -> 0.5885118390389538
2126/3780 0.300 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.561158839742289
2127/3780 0.300 0.040 1.0 StandardScaler() 0 -> 0.7626581365824762
2128/3780 0.300 0.040 1.0 MinMaxScaler() 0 -> 0.5280635940895596
2129/3780 0.300 0.051 scale StandardScaler() 0 -> 0.5175958129231534
2130/3780 0.300 0.051 scale MinMaxScaler() 0 -> 0.5147308994403935
2131/3780 0.300 0.051 auto StandardScaler() 0 -> 0.5175958129231534
2132/3780 0.300 0.051 auto MinMaxScaler() 0 -> 0.6013465109996287
2133/3780 0.300 0.051 0.01 StandardScaler() 0 -> 0.5617983304744752
2134/3780 0.300 0.051 0.01 MinMaxScaler() 0 -> 0.7565956623421353
2135/3780 0.300 0.051 0.03162277660168379 StandardScaler() 0 -> 0.527035686128294
2136/3780 0.300 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6809823214298986
2137/3780 0.300 0.051 0.1 StandardScaler() 0 -> 0.5185742577096398
2138/3780 0.300 0.051 0.1 MinMaxScaler() 0 -> 0.5971201094834969
2139/3780 0.300 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5733744699213833
2140/3780 0.300 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5536655919197845
2141/3780 0.300 0.051 1.0 StandardScaler() 0 -> 0.7530636854814468
2142/3780 0.300 0.051 1.0 MinMaxScaler() 0 -> 0.5230819055093936
2143/3780 0.300 0.065 scale StandardScaler() 0 -> 0.5111996104690165
2144/3780 0.300 0.065 scale MinMaxScaler() 0 -> 0.5098320919030336
2145/3780 0.300 0.065 auto StandardScaler() 0 -> 0.5111996104690166
2146/3780 0.300 0.065 auto MinMaxScaler() 0 -> 0.5900916673663662
2147/3780 0.300 0.065 0.01 StandardScaler() 0 -> 0.5546807922682042
2148/3780 0.300 0.065 0.01 MinMaxScaler() 0 -> 0.7455431806737551
2149/3780 0.300 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5217245929106494
2150/3780 0.300 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6583412284373259
2151/3780 0.300 0.065 0.1 StandardScaler() 0 -> 0.5116700684097442
2152/3780 0.300 0.065 0.1 MinMaxScaler() 0 -> 0.5855585507641753
2153/3780 0.300 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5593907422401295
2154/3780 0.300 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5479015855531811
2155/3780 0.300 0.065 1.0 StandardScaler() 0 -> 0.7414698840168747
2156/3780 0.300 0.065 1.0 MinMaxScaler() 0 -> 0.5177243703738531
2157/3780 0.300 0.082 scale StandardScaler() 0 -> 0.5047779685235412
2158/3780 0.300 0.082 scale MinMaxScaler() 0 -> 0.5053236005579782
2159/3780 0.300 0.082 auto StandardScaler() 0 -> 0.5047779685235412
2160/3780 0.300 0.082 auto MinMaxScaler() 0 -> 0.5798061421115609
2161/3780 0.300 0.082 0.01 StandardScaler() 0 -> 0.5484264712267511
2162/3780 0.300 0.082 0.01 MinMaxScaler() 0 -> 0.7321215470499642
2163/3780 0.300 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5158497054320569
2164/3780 0.300 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6361857022809506
2165/3780 0.300 0.082 0.1 StandardScaler() 0 -> 0.504884583635483
2166/3780 0.300 0.082 0.1 MinMaxScaler() 0 -> 0.5766416787174798
2167/3780 0.300 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5459379169708932
2168/3780 0.300 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5427793247356814
2169/3780 0.300 0.082 1.0 StandardScaler() 0 -> 0.7276050254413131
2170/3780 0.300 0.082 1.0 MinMaxScaler() 0 -> 0.5130397955357425
2171/3780 0.300 0.104 scale StandardScaler() 0 -> 0.49935530357274965
2172/3780 0.300 0.104 scale MinMaxScaler() 0 -> 0.5004219415751142
2173/3780 0.300 0.104 auto StandardScaler() 0 -> 0.49935530357274965
2174/3780 0.300 0.104 auto MinMaxScaler() 0 -> 0.5723597364892418
2175/3780 0.300 0.104 0.01 StandardScaler() 0 -> 0.5428255275228251
2176/3780 0.300 0.104 0.01 MinMaxScaler() 0 -> 0.7160671180337257
2177/3780 0.300 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5103423479689041
2178/3780 0.300 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6190686889802247
2179/3780 0.300 0.104 0.1 StandardScaler() 0 -> 0.4992647058860546
2180/3780 0.300 0.104 0.1 MinMaxScaler() 0 -> 0.5697060979467093
2181/3780 0.300 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5327675404750781
2182/3780 0.300 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5374874215386197
2183/3780 0.300 0.104 1.0 StandardScaler() 0 -> 0.7110725306375385
2184/3780 0.300 0.104 1.0 MinMaxScaler() 0 -> 0.5087124377845037
2185/3780 0.300 0.132 scale StandardScaler() 0 -> 0.49402966883516664
2186/3780 0.300 0.132 scale MinMaxScaler() 0 -> 0.4960131037554815
2187/3780 0.300 0.132 auto StandardScaler() 0 -> 0.49402966883516664
2188/3780 0.300 0.132 auto MinMaxScaler() 0 -> 0.5651371056378612
2189/3780 0.300 0.132 0.01 StandardScaler() 0 -> 0.5373902439367733
2190/3780 0.300 0.132 0.01 MinMaxScaler() 0 -> 0.6972465662196473
2191/3780 0.300 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5061453999206132
2192/3780 0.300 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6052689800660099
2193/3780 0.300 0.132 0.1 StandardScaler() 0 -> 0.49422948858574745
2194/3780 0.300 0.132 0.1 MinMaxScaler() 0 -> 0.5623677576935345
2195/3780 0.300 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5213204020132592
2196/3780 0.300 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5324161236690806
2197/3780 0.300 0.132 1.0 StandardScaler() 0 -> 0.6915471970870062
2198/3780 0.300 0.132 1.0 MinMaxScaler() 0 -> 0.5051671505423884
2199/3780 0.300 0.168 scale StandardScaler() 0 -> 0.49002579470581736
2200/3780 0.300 0.168 scale MinMaxScaler() 0 -> 0.49189410882751883
2201/3780 0.300 0.168 auto StandardScaler() 0 -> 0.4900257947058175
2202/3780 0.300 0.168 auto MinMaxScaler() 0 -> 0.5598126433590317
2203/3780 0.300 0.168 0.01 StandardScaler() 0 -> 0.531893912882314
2204/3780 0.300 0.168 0.01 MinMaxScaler() 0 -> 0.6758594675544279
2205/3780 0.300 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5020551337258392
2206/3780 0.300 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.5945734021078984
2207/3780 0.300 0.168 0.1 StandardScaler() 0 -> 0.4900887070681936
2208/3780 0.300 0.168 0.1 MinMaxScaler() 0 -> 0.5573741615039612
2209/3780 0.300 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5115956392312793
2210/3780 0.300 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5285261714244788
2211/3780 0.300 0.168 1.0 StandardScaler() 0 -> 0.669215459867898
2212/3780 0.300 0.168 1.0 MinMaxScaler() 0 -> 0.5015545025023496
2213/3780 0.300 0.213 scale StandardScaler() 0 -> 0.48673848588921037
2214/3780 0.300 0.213 scale MinMaxScaler() 0 -> 0.4883620105029099
2215/3780 0.300 0.213 auto StandardScaler() 0 -> 0.48673848588921037
2216/3780 0.300 0.213 auto MinMaxScaler() 0 -> 0.5555596014808244
2217/3780 0.300 0.213 0.01 StandardScaler() 0 -> 0.527263118990696
2218/3780 0.300 0.213 0.01 MinMaxScaler() 0 -> 0.6530060338895584
2219/3780 0.300 0.213 0.03162277660168379 StandardScaler() 0 -> 0.49966969812293116
2220/3780 0.300 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5841718020782439
2221/3780 0.300 0.213 0.1 StandardScaler() 0 -> 0.48670291617390243
2222/3780 0.300 0.213 0.1 MinMaxScaler() 0 -> 0.553626064115789
2223/3780 0.300 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5022411906835256
2224/3780 0.300 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5246119557954972
2225/3780 0.300 0.213 1.0 StandardScaler() 0 -> 0.6438612314471294
2226/3780 0.300 0.213 1.0 MinMaxScaler() 0 -> 0.49848546854794645
2227/3780 0.300 0.270 scale StandardScaler() 0 -> 0.4839094824406396
2228/3780 0.300 0.270 scale MinMaxScaler() 0 -> 0.48569312224225936
2229/3780 0.300 0.270 auto StandardScaler() 0 -> 0.4839094824406395
2230/3780 0.300 0.270 auto MinMaxScaler() 0 -> 0.5518441621634739
2231/3780 0.300 0.270 0.01 StandardScaler() 0 -> 0.5236026240429256
2232/3780 0.300 0.270 0.01 MinMaxScaler() 0 -> 0.6320304007621316
2233/3780 0.300 0.270 0.03162277660168379 StandardScaler() 0 -> 0.4964572529251156
2234/3780 0.300 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5761416545815017
2235/3780 0.300 0.270 0.1 StandardScaler() 0 -> 0.4837260625372825
2236/3780 0.300 0.270 0.1 MinMaxScaler() 0 -> 0.5496726923889792
2237/3780 0.300 0.270 0.31622776601683794 StandardScaler() 0 -> 0.49377927777942593
2238/3780 0.300 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5210125451959436
2239/3780 0.300 0.270 1.0 StandardScaler() 0 -> 0.6166339289061996
2240/3780 0.300 0.270 1.0 MinMaxScaler() 0 -> 0.49597701743601075
2241/3780 0.300 0.342 scale StandardScaler() 0 -> 0.48145244449629626
2242/3780 0.300 0.342 scale MinMaxScaler() 0 -> 0.4832335298628157
2243/3780 0.300 0.342 auto StandardScaler() 0 -> 0.48145244449629626
2244/3780 0.300 0.342 auto MinMaxScaler() 0 -> 0.547997840002682
2245/3780 0.300 0.342 0.01 StandardScaler() 0 -> 0.5199082534823655
2246/3780 0.300 0.342 0.01 MinMaxScaler() 0 -> 0.6161206985935993
2247/3780 0.300 0.342 0.03162277660168379 StandardScaler() 0 -> 0.4941360240326788
2248/3780 0.300 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5695422886714135
2249/3780 0.300 0.342 0.1 StandardScaler() 0 -> 0.4811462093717247
2250/3780 0.300 0.342 0.1 MinMaxScaler() 0 -> 0.5463989656019929
2251/3780 0.300 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4858561804614303
2252/3780 0.300 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5175380445330909
2253/3780 0.300 0.342 1.0 StandardScaler() 0 -> 0.5896848782592886
2254/3780 0.300 0.342 1.0 MinMaxScaler() 0 -> 0.493077201977475
2255/3780 0.300 0.434 scale StandardScaler() 0 -> 0.47922108990175344
2256/3780 0.300 0.434 scale MinMaxScaler() 0 -> 0.4812377599186876
2257/3780 0.300 0.434 auto StandardScaler() 0 -> 0.4792210899017533
2258/3780 0.300 0.434 auto MinMaxScaler() 0 -> 0.5450889304321817
2259/3780 0.300 0.434 0.01 StandardScaler() 0 -> 0.5163690091641319
2260/3780 0.300 0.434 0.01 MinMaxScaler() 0 -> 0.6031484267369979
2261/3780 0.300 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49099547406294813
2262/3780 0.300 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.563693591521745
2263/3780 0.300 0.434 0.1 StandardScaler() 0 -> 0.4784974456110251
2264/3780 0.300 0.434 0.1 MinMaxScaler() 0 -> 0.5431449707132789
2265/3780 0.300 0.434 0.31622776601683794 StandardScaler() 0 -> 0.478975818304382
2266/3780 0.300 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.514311333293955
2267/3780 0.300 0.434 1.0 StandardScaler() 0 -> 0.5635332773849574
2268/3780 0.300 0.434 1.0 MinMaxScaler() 0 -> 0.490098476311761
2269/3780 0.300 0.551 scale StandardScaler() 0 -> 0.47688770725064106
2270/3780 0.300 0.551 scale MinMaxScaler() 0 -> 0.4789998879651696
2271/3780 0.300 0.551 auto StandardScaler() 0 -> 0.47688770725064106
2272/3780 0.300 0.551 auto MinMaxScaler() 0 -> 0.5422784837112979
2273/3780 0.300 0.551 0.01 StandardScaler() 0 -> 0.5128625922316726
2274/3780 0.300 0.551 0.01 MinMaxScaler() 0 -> 0.5924568450849627
2275/3780 0.300 0.551 0.03162277660168379 StandardScaler() 0 -> 0.48845819033017657
2276/3780 0.300 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.559675655215073
2277/3780 0.300 0.551 0.1 StandardScaler() 0 -> 0.47618967061863593
2278/3780 0.300 0.551 0.1 MinMaxScaler() 0 -> 0.5402276106321321
2279/3780 0.300 0.551 0.31622776601683794 StandardScaler() 0 -> 0.4737163590656737
2280/3780 0.300 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.510559518962606
2281/3780 0.300 0.551 1.0 StandardScaler() 0 -> 0.5397085206896689
2282/3780 0.300 0.551 1.0 MinMaxScaler() 0 -> 0.4883774614559204
2283/3780 0.300 0.700 scale StandardScaler() 0 -> 0.4749511416545367
2284/3780 0.300 0.700 scale MinMaxScaler() 0 -> 0.4762760658091971
2285/3780 0.300 0.700 auto StandardScaler() 0 -> 0.4749511416545367
2286/3780 0.300 0.700 auto MinMaxScaler() 0 -> 0.5394794228652482
2287/3780 0.300 0.700 0.01 StandardScaler() 0 -> 0.5090264259490345
2288/3780 0.300 0.700 0.01 MinMaxScaler() 0 -> 0.5829514286821006
2289/3780 0.300 0.700 0.03162277660168379 StandardScaler() 0 -> 0.48646804806255334
2290/3780 0.300 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5567518154720337
2291/3780 0.300 0.700 0.1 StandardScaler() 0 -> 0.47379665407896937
2292/3780 0.300 0.700 0.1 MinMaxScaler() 0 -> 0.537438356046622
2293/3780 0.300 0.700 0.31622776601683794 StandardScaler() 0 -> 0.4692050158166478
2294/3780 0.300 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5071949901314977
2295/3780 0.300 0.700 1.0 StandardScaler() 0 -> 0.5223024002121848
2296/3780 0.300 0.700 1.0 MinMaxScaler() 0 -> 0.4869461776998132
2297/3780 0.300 0.888 scale StandardScaler() 0 -> 0.473336216241836
2298/3780 0.300 0.888 scale MinMaxScaler() 0 -> 0.4739533788122321
2299/3780 0.300 0.888 auto StandardScaler() 0 -> 0.47333621624183575
2300/3780 0.300 0.888 auto MinMaxScaler() 0 -> 0.5368753453005045
2301/3780 0.300 0.888 0.01 StandardScaler() 0 -> 0.5060747634182764
2302/3780 0.300 0.888 0.01 MinMaxScaler() 0 -> 0.5751547200123482
2303/3780 0.300 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4852820290839905
2304/3780 0.300 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5538233802860622
2305/3780 0.300 0.888 0.1 StandardScaler() 0 -> 0.4724736880414196
2306/3780 0.300 0.888 0.1 MinMaxScaler() 0 -> 0.5343483038598191
2307/3780 0.300 0.888 0.31622776601683794 StandardScaler() 0 -> 0.4663103033049838
2308/3780 0.300 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.505003383364187
2309/3780 0.300 0.888 1.0 StandardScaler() 0 -> 0.5131443073722973
2310/3780 0.300 0.888 1.0 MinMaxScaler() 0 -> 0.4849697853307124
2311/3780 0.300 1.126 scale StandardScaler() 0 -> 0.47214451155127307
2312/3780 0.300 1.126 scale MinMaxScaler() 0 -> 0.4723845777232165
2313/3780 0.300 1.126 auto StandardScaler() 0 -> 0.47214451155127274
2314/3780 0.300 1.126 auto MinMaxScaler() 0 -> 0.5336174449516438
2315/3780 0.300 1.126 0.01 StandardScaler() 0 -> 0.5030473835930435
2316/3780 0.300 1.126 0.01 MinMaxScaler() 0 -> 0.5687591603192298
2317/3780 0.300 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48413617474687837
2318/3780 0.300 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5514697761847045
2319/3780 0.300 1.126 0.1 StandardScaler() 0 -> 0.47116967701731566
2320/3780 0.300 1.126 0.1 MinMaxScaler() 0 -> 0.5314983682170011
2321/3780 0.300 1.126 0.31622776601683794 StandardScaler() 0 -> 0.4649622264525844
2322/3780 0.300 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5023559267456631
2323/3780 0.300 1.126 1.0 StandardScaler() 0 -> 0.508001760835214
2324/3780 0.300 1.126 1.0 MinMaxScaler() 0 -> 0.48335373065151305
2325/3780 0.300 1.429 scale StandardScaler() 0 -> 0.471454393924631
2326/3780 0.300 1.429 scale MinMaxScaler() 0 -> 0.47140454593399556
2327/3780 0.300 1.429 auto StandardScaler() 0 -> 0.471454393924631
2328/3780 0.300 1.429 auto MinMaxScaler() 0 -> 0.5306860800463574
2329/3780 0.300 1.429 0.01 StandardScaler() 0 -> 0.5004227011786857
2330/3780 0.300 1.429 0.01 MinMaxScaler() 0 -> 0.5639223217337103
2331/3780 0.300 1.429 0.03162277660168379 StandardScaler() 0 -> 0.4835063307549308
2332/3780 0.300 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5496002484663265
2333/3780 0.300 1.429 0.1 StandardScaler() 0 -> 0.47080170900893625
2334/3780 0.300 1.429 0.1 MinMaxScaler() 0 -> 0.5276244917992
2335/3780 0.300 1.429 0.31622776601683794 StandardScaler() 0 -> 0.46392260103201094
2336/3780 0.300 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.4991952465180323
2337/3780 0.300 1.429 1.0 StandardScaler() 0 -> 0.5039546840538818
2338/3780 0.300 1.429 1.0 MinMaxScaler() 0 -> 0.4818330375760418
2339/3780 0.300 1.814 scale StandardScaler() 0 -> 0.47127514663388176
2340/3780 0.300 1.814 scale MinMaxScaler() 0 -> 0.47139121384804844
2341/3780 0.300 1.814 auto StandardScaler() 0 -> 0.47127514663388165
2342/3780 0.300 1.814 auto MinMaxScaler() 0 -> 0.5267988060101356
2343/3780 0.300 1.814 0.01 StandardScaler() 0 -> 0.49797496890184606
2344/3780 0.300 1.814 0.01 MinMaxScaler() 0 -> 0.560232892368041
2345/3780 0.300 1.814 0.03162277660168379 StandardScaler() 0 -> 0.4822066717025493
2346/3780 0.300 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5479342701304026
2347/3780 0.300 1.814 0.1 StandardScaler() 0 -> 0.4699894897812287
2348/3780 0.300 1.814 0.1 MinMaxScaler() 0 -> 0.5244158129250446
2349/3780 0.300 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4655679265655848
2350/3780 0.300 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.49718439560999833
2351/3780 0.300 1.814 1.0 StandardScaler() 0 -> 0.5022140594836868
2352/3780 0.300 1.814 1.0 MinMaxScaler() 0 -> 0.48023944115936273
2353/3780 0.300 2.302 scale StandardScaler() 0 -> 0.4704929621097353
2354/3780 0.300 2.302 scale MinMaxScaler() 0 -> 0.47186541372118107
2355/3780 0.300 2.302 auto StandardScaler() 0 -> 0.4704929621097347
2356/3780 0.300 2.302 auto MinMaxScaler() 0 -> 0.5240431674762557
2357/3780 0.300 2.302 0.01 StandardScaler() 0 -> 0.4957831590524921
2358/3780 0.300 2.302 0.01 MinMaxScaler() 0 -> 0.5573178952662287
2359/3780 0.300 2.302 0.03162277660168379 StandardScaler() 0 -> 0.48110593137307656
2360/3780 0.300 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5465800339887831
2361/3780 0.300 2.302 0.1 StandardScaler() 0 -> 0.4693313911739583
2362/3780 0.300 2.302 0.1 MinMaxScaler() 0 -> 0.5218564468329644
2363/3780 0.300 2.302 0.31622776601683794 StandardScaler() 0 -> 0.46863264622756223
2364/3780 0.300 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.49505336618325585
2365/3780 0.300 2.302 1.0 StandardScaler() 0 -> 0.5018408945213745
2366/3780 0.300 2.302 1.0 MinMaxScaler() 0 -> 0.47901168156164337
2367/3780 0.300 2.921 scale StandardScaler() 0 -> 0.4704177891864765
2368/3780 0.300 2.921 scale MinMaxScaler() 0 -> 0.47199350376332777
2369/3780 0.300 2.921 auto StandardScaler() 0 -> 0.4704177891864772
2370/3780 0.300 2.921 auto MinMaxScaler() 0 -> 0.5213379041973992
2371/3780 0.300 2.921 0.01 StandardScaler() 0 -> 0.4945169211037346
2372/3780 0.300 2.921 0.01 MinMaxScaler() 0 -> 0.5553917778981293
2373/3780 0.300 2.921 0.03162277660168379 StandardScaler() 0 -> 0.4803033173785804
2374/3780 0.300 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5450623795278097
2375/3780 0.300 2.921 0.1 StandardScaler() 0 -> 0.4693552301390658
2376/3780 0.300 2.921 0.1 MinMaxScaler() 0 -> 0.5185571532337635
2377/3780 0.300 2.921 0.31622776601683794 StandardScaler() 0 -> 0.47194053142327314
2378/3780 0.300 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49325723330503674
2379/3780 0.300 2.921 1.0 StandardScaler() 0 -> 0.501717361941421
2380/3780 0.300 2.921 1.0 MinMaxScaler() 0 -> 0.47803387117862295
2381/3780 0.300 3.707 scale StandardScaler() 0 -> 0.470879892356816
2382/3780 0.300 3.707 scale MinMaxScaler() 0 -> 0.4728518813138189
2383/3780 0.300 3.707 auto StandardScaler() 0 -> 0.47087989235681577
2384/3780 0.300 3.707 auto MinMaxScaler() 0 -> 0.5181247142907836
2385/3780 0.300 3.707 0.01 StandardScaler() 0 -> 0.4932834482573652
2386/3780 0.300 3.707 0.01 MinMaxScaler() 0 -> 0.5535178233556818
2387/3780 0.300 3.707 0.03162277660168379 StandardScaler() 0 -> 0.47950995577079397
2388/3780 0.300 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5430623089082679
2389/3780 0.300 3.707 0.1 StandardScaler() 0 -> 0.4702903208868745
2390/3780 0.300 3.707 0.1 MinMaxScaler() 0 -> 0.5154828154519907
2391/3780 0.300 3.707 0.31622776601683794 StandardScaler() 0 -> 0.4768835126148398
2392/3780 0.300 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4918336487102864
2393/3780 0.300 3.707 1.0 StandardScaler() 0 -> 0.5017289250082165
2394/3780 0.300 3.707 1.0 MinMaxScaler() 0 -> 0.47722605050681005
2395/3780 0.300 4.703 scale StandardScaler() 0 -> 0.47233811527405406
2396/3780 0.300 4.703 scale MinMaxScaler() 0 -> 0.4738182747441257
2397/3780 0.300 4.703 auto StandardScaler() 0 -> 0.4723381152740536
2398/3780 0.300 4.703 auto MinMaxScaler() 0 -> 0.5148490038993186
2399/3780 0.300 4.703 0.01 StandardScaler() 0 -> 0.4921850983531237
2400/3780 0.300 4.703 0.01 MinMaxScaler() 0 -> 0.5524997271662678
2401/3780 0.300 4.703 0.03162277660168379 StandardScaler() 0 -> 0.4781913568023007
2402/3780 0.300 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5408728708817981
2403/3780 0.300 4.703 0.1 StandardScaler() 0 -> 0.4729750494359337
2404/3780 0.300 4.703 0.1 MinMaxScaler() 0 -> 0.5118197132967813
2405/3780 0.300 4.703 0.31622776601683794 StandardScaler() 0 -> 0.48170807613505917
2406/3780 0.300 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.49125137053566365
2407/3780 0.300 4.703 1.0 StandardScaler() 0 -> 0.5017352440249349
2408/3780 0.300 4.703 1.0 MinMaxScaler() 0 -> 0.476253726154567
2409/3780 0.300 5.968 scale StandardScaler() 0 -> 0.47519399614870594
2410/3780 0.300 5.968 scale MinMaxScaler() 0 -> 0.47425786628687266
2411/3780 0.300 5.968 auto StandardScaler() 0 -> 0.4751939961487055
2412/3780 0.300 5.968 auto MinMaxScaler() 0 -> 0.511405346938106
2413/3780 0.300 5.968 0.01 StandardScaler() 0 -> 0.49165332797288136
2414/3780 0.300 5.968 0.01 MinMaxScaler() 0 -> 0.5518663194638204
2415/3780 0.300 5.968 0.03162277660168379 StandardScaler() 0 -> 0.4776341085798072
2416/3780 0.300 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.538507535113924
2417/3780 0.300 5.968 0.1 StandardScaler() 0 -> 0.4761056853483467
2418/3780 0.300 5.968 0.1 MinMaxScaler() 0 -> 0.5092826054501132
2419/3780 0.300 5.968 0.31622776601683794 StandardScaler() 0 -> 0.4874342954173207
2420/3780 0.300 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.49070485036526995
2421/3780 0.300 5.968 1.0 StandardScaler() 0 -> 0.501740160463844
2422/3780 0.300 5.968 1.0 MinMaxScaler() 0 -> 0.47562431201511285
2423/3780 0.300 7.574 scale StandardScaler() 0 -> 0.4788457854305436
2424/3780 0.300 7.574 scale MinMaxScaler() 0 -> 0.4763063043068137
2425/3780 0.300 7.574 auto StandardScaler() 0 -> 0.478845785430543
2426/3780 0.300 7.574 auto MinMaxScaler() 0 -> 0.5087985958272004
2427/3780 0.300 7.574 0.01 StandardScaler() 0 -> 0.49081984973611475
2428/3780 0.300 7.574 0.01 MinMaxScaler() 0 -> 0.5513201618592399
2429/3780 0.300 7.574 0.03162277660168379 StandardScaler() 0 -> 0.47768442800622674
2430/3780 0.300 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5359564286100454
2431/3780 0.300 7.574 0.1 StandardScaler() 0 -> 0.48084001905944335
2432/3780 0.300 7.574 0.1 MinMaxScaler() 0 -> 0.507066765119704
2433/3780 0.300 7.574 0.31622776601683794 StandardScaler() 0 -> 0.49183090930624934
2434/3780 0.300 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.48992929551391323
2435/3780 0.300 7.574 1.0 StandardScaler() 0 -> 0.5017399932216955
2436/3780 0.300 7.574 1.0 MinMaxScaler() 0 -> 0.47605346148353583
2437/3780 0.300 9.611 scale StandardScaler() 0 -> 0.48352088066273025
2438/3780 0.300 9.611 scale MinMaxScaler() 0 -> 0.47975586482531024
2439/3780 0.300 9.611 auto StandardScaler() 0 -> 0.48352088066272797
2440/3780 0.300 9.611 auto MinMaxScaler() 0 -> 0.506483059957065
2441/3780 0.300 9.611 0.01 StandardScaler() 0 -> 0.49056332607517933
2442/3780 0.300 9.611 0.01 MinMaxScaler() 0 -> 0.5505566447725544
2443/3780 0.300 9.611 0.03162277660168379 StandardScaler() 0 -> 0.477853020709711
2444/3780 0.300 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5329282857882326
2445/3780 0.300 9.611 0.1 StandardScaler() 0 -> 0.4890155673752943
2446/3780 0.300 9.611 0.1 MinMaxScaler() 0 -> 0.5044144957160311
2447/3780 0.300 9.611 0.31622776601683794 StandardScaler() 0 -> 0.49606590138347967
2448/3780 0.300 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4893270280839452
2449/3780 0.300 9.611 1.0 StandardScaler() 0 -> 0.5017410981188717
2450/3780 0.300 9.611 1.0 MinMaxScaler() 0 -> 0.4763880416104886
2451/3780 0.300 12.196 scale StandardScaler() 0 -> 0.4912745035159866
2452/3780 0.300 12.196 scale MinMaxScaler() 0 -> 0.48312349843804
2453/3780 0.300 12.196 auto StandardScaler() 0 -> 0.49127450351598584
2454/3780 0.300 12.196 auto MinMaxScaler() 0 -> 0.5038636910888616
2455/3780 0.300 12.196 0.01 StandardScaler() 0 -> 0.4898993791713852
2456/3780 0.300 12.196 0.01 MinMaxScaler() 0 -> 0.5494463480363828
2457/3780 0.300 12.196 0.03162277660168379 StandardScaler() 0 -> 0.47837065277569346
2458/3780 0.300 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5298096259841824
2459/3780 0.300 12.196 0.1 StandardScaler() 0 -> 0.4989835967572891
2460/3780 0.300 12.196 0.1 MinMaxScaler() 0 -> 0.5017429826187844
2461/3780 0.300 12.196 0.31622776601683794 StandardScaler() 0 -> 0.49914421131870795
2462/3780 0.300 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4888869403802749
2463/3780 0.300 12.196 1.0 StandardScaler() 0 -> 0.5017410981188717
2464/3780 0.300 12.196 1.0 MinMaxScaler() 0 -> 0.47657936689130703
2465/3780 0.300 15.476 scale StandardScaler() 0 -> 0.5027273604249735
2466/3780 0.300 15.476 scale MinMaxScaler() 0 -> 0.48875945940860926
2467/3780 0.300 15.476 auto StandardScaler() 0 -> 0.5027273604249727
2468/3780 0.300 15.476 auto MinMaxScaler() 0 -> 0.5015177207324049
2469/3780 0.300 15.476 0.01 StandardScaler() 0 -> 0.48941246945310213
2470/3780 0.300 15.476 0.01 MinMaxScaler() 0 -> 0.5483056822710649
2471/3780 0.300 15.476 0.03162277660168379 StandardScaler() 0 -> 0.47902003193571546
2472/3780 0.300 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5266476491140714
2473/3780 0.300 15.476 0.1 StandardScaler() 0 -> 0.510591054809164
2474/3780 0.300 15.476 0.1 MinMaxScaler() 0 -> 0.5001476217651996
2475/3780 0.300 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5017360487472492
2476/3780 0.300 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.4882491899043026
2477/3780 0.300 15.476 1.0 StandardScaler() 0 -> 0.5017410981188717
2478/3780 0.300 15.476 1.0 MinMaxScaler() 0 -> 0.47693255476131585
2479/3780 0.300 19.638 scale StandardScaler() 0 -> 0.5158683392356246
2480/3780 0.300 19.638 scale MinMaxScaler() 0 -> 0.4973546425391559
2481/3780 0.300 19.638 auto StandardScaler() 0 -> 0.515868339235619
2482/3780 0.300 19.638 auto MinMaxScaler() 0 -> 0.5001872097443482
2483/3780 0.300 19.638 0.01 StandardScaler() 0 -> 0.4890434117910723
2484/3780 0.300 19.638 0.01 MinMaxScaler() 0 -> 0.547186195717212
2485/3780 0.300 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4802393210236597
2486/3780 0.300 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5239666420593648
2487/3780 0.300 19.638 0.1 StandardScaler() 0 -> 0.5256013655476138
2488/3780 0.300 19.638 0.1 MinMaxScaler() 0 -> 0.4983311159455379
2489/3780 0.300 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5042536896175628
2490/3780 0.300 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.48718698991413634
2491/3780 0.300 19.638 1.0 StandardScaler() 0 -> 0.5017410981188717
2492/3780 0.300 19.638 1.0 MinMaxScaler() 0 -> 0.4778112097438747
2493/3780 0.300 24.920 scale StandardScaler() 0 -> 0.5313411810790262
2494/3780 0.300 24.920 scale MinMaxScaler() 0 -> 0.5078845878898465
2495/3780 0.300 24.920 auto StandardScaler() 0 -> 0.5313411810790284
2496/3780 0.300 24.920 auto MinMaxScaler() 0 -> 0.49822362857275987
2497/3780 0.300 24.920 0.01 StandardScaler() 0 -> 0.48816916200632504
2498/3780 0.300 24.920 0.01 MinMaxScaler() 0 -> 0.5455366013831081
2499/3780 0.300 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4821148543006461
2500/3780 0.300 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5210449005200753
2501/3780 0.300 24.920 0.1 StandardScaler() 0 -> 0.5423087492026393
2502/3780 0.300 24.920 0.1 MinMaxScaler() 0 -> 0.49705907015586487
2503/3780 0.300 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5051900735510965
2504/3780 0.300 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.4862422816907026
2505/3780 0.300 24.920 1.0 StandardScaler() 0 -> 0.5017410981188717
2506/3780 0.300 24.920 1.0 MinMaxScaler() 0 -> 0.4802129528121122
2507/3780 0.300 31.623 scale StandardScaler() 0 -> 0.5494465709966122
2508/3780 0.300 31.623 scale MinMaxScaler() 0 -> 0.5207185458903869
2509/3780 0.300 31.623 auto StandardScaler() 0 -> 0.549446570996611
2510/3780 0.300 31.623 auto MinMaxScaler() 0 -> 0.4970537014523099
2511/3780 0.300 31.623 0.01 StandardScaler() 0 -> 0.4871712029041491
2512/3780 0.300 31.623 0.01 MinMaxScaler() 0 -> 0.5438690411826638
2513/3780 0.300 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4849459903217183
2514/3780 0.300 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5177071497758486
2515/3780 0.300 31.623 0.1 StandardScaler() 0 -> 0.5614386529582956
2516/3780 0.300 31.623 0.1 MinMaxScaler() 0 -> 0.4959070174661633
2517/3780 0.300 31.623 0.31622776601683794 StandardScaler() 0 -> 0.505743860095687
2518/3780 0.300 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4857667368364209
2519/3780 0.300 31.623 1.0 StandardScaler() 0 -> 0.5017410981188717
2520/3780 0.300 31.623 1.0 MinMaxScaler() 0 -> 0.4829850131311355
2521/3780 0.350 0.032 scale StandardScaler() 0 -> 0.5351982855846693
2522/3780 0.350 0.032 scale MinMaxScaler() 0 -> 0.53177759652953
2523/3780 0.350 0.032 auto StandardScaler() 0 -> 0.5351982855846693
2524/3780 0.350 0.032 auto MinMaxScaler() 0 -> 0.6358066677393087
2525/3780 0.350 0.032 0.01 StandardScaler() 0 -> 0.5808957754380176
2526/3780 0.350 0.032 0.01 MinMaxScaler() 0 -> 0.7946676640726226
2527/3780 0.350 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5431308376852377
2528/3780 0.350 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7374243834120708
2529/3780 0.350 0.032 0.1 StandardScaler() 0 -> 0.5368521397717742
2530/3780 0.350 0.032 0.1 MinMaxScaler() 0 -> 0.6269109274770139
2531/3780 0.350 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6124787813413731
2532/3780 0.350 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5699198293583766
2533/3780 0.350 0.032 1.0 StandardScaler() 0 -> 0.794533337443765
2534/3780 0.350 0.032 1.0 MinMaxScaler() 0 -> 0.537578669860949
2535/3780 0.350 0.040 scale StandardScaler() 0 -> 0.5294483797177529
2536/3780 0.350 0.040 scale MinMaxScaler() 0 -> 0.5257611931831389
2537/3780 0.350 0.040 auto StandardScaler() 0 -> 0.5294483797177528
2538/3780 0.350 0.040 auto MinMaxScaler() 0 -> 0.6154335862795959
2539/3780 0.350 0.040 0.01 StandardScaler() 0 -> 0.5715926500198552
2540/3780 0.350 0.040 0.01 MinMaxScaler() 0 -> 0.7867995311998913
2541/3780 0.350 0.040 0.03162277660168379 StandardScaler() 0 -> 0.537176109876755
2542/3780 0.350 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7175338939297844
2543/3780 0.350 0.040 0.1 StandardScaler() 0 -> 0.5303365078717593
2544/3780 0.350 0.040 0.1 MinMaxScaler() 0 -> 0.6092253057113403
2545/3780 0.350 0.040 0.31622776601683794 StandardScaler() 0 -> 0.595525645762344
2546/3780 0.350 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5617157778555341
2547/3780 0.350 0.040 1.0 StandardScaler() 0 -> 0.7868073715632072
2548/3780 0.350 0.040 1.0 MinMaxScaler() 0 -> 0.5323984650282858
2549/3780 0.350 0.051 scale StandardScaler() 0 -> 0.5220039983324075
2550/3780 0.350 0.051 scale MinMaxScaler() 0 -> 0.5200389890397468
2551/3780 0.350 0.051 auto StandardScaler() 0 -> 0.5220039983324075
2552/3780 0.350 0.051 auto MinMaxScaler() 0 -> 0.6004775886156343
2553/3780 0.350 0.051 0.01 StandardScaler() 0 -> 0.5631864974049821
2554/3780 0.350 0.051 0.01 MinMaxScaler() 0 -> 0.7770972840487581
2555/3780 0.350 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5309622555241476
2556/3780 0.350 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.6945301368782072
2557/3780 0.350 0.051 0.1 StandardScaler() 0 -> 0.5226500431038721
2558/3780 0.350 0.051 0.1 MinMaxScaler() 0 -> 0.5958481261480143
2559/3780 0.350 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5796507771581777
2560/3780 0.350 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5554496126945452
2561/3780 0.350 0.051 1.0 StandardScaler() 0 -> 0.7773791212616183
2562/3780 0.350 0.051 1.0 MinMaxScaler() 0 -> 0.5269591743010525
2563/3780 0.350 0.065 scale StandardScaler() 0 -> 0.5149096072025282
2564/3780 0.350 0.065 scale MinMaxScaler() 0 -> 0.5147943432606039
2565/3780 0.350 0.065 auto StandardScaler() 0 -> 0.5149096072025282
2566/3780 0.350 0.065 auto MinMaxScaler() 0 -> 0.5897400157204916
2567/3780 0.350 0.065 0.01 StandardScaler() 0 -> 0.5560198412678444
2568/3780 0.350 0.065 0.01 MinMaxScaler() 0 -> 0.7651603159834903
2569/3780 0.350 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5250810891808881
2570/3780 0.350 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6689361314125207
2571/3780 0.350 0.065 0.1 StandardScaler() 0 -> 0.5151371936382353
2572/3780 0.350 0.065 0.1 MinMaxScaler() 0 -> 0.5858934171052202
2573/3780 0.350 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5649225541996916
2574/3780 0.350 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5497781455493108
2575/3780 0.350 0.065 1.0 StandardScaler() 0 -> 0.7659381792775167
2576/3780 0.350 0.065 1.0 MinMaxScaler() 0 -> 0.5217447174090631
2577/3780 0.350 0.082 scale StandardScaler() 0 -> 0.508711618053313
2578/3780 0.350 0.082 scale MinMaxScaler() 0 -> 0.5089454581279914
2579/3780 0.350 0.082 auto StandardScaler() 0 -> 0.508711618053313
2580/3780 0.350 0.082 auto MinMaxScaler() 0 -> 0.5811434322495712
2581/3780 0.350 0.082 0.01 StandardScaler() 0 -> 0.5499212667955194
2582/3780 0.350 0.082 0.01 MinMaxScaler() 0 -> 0.750616303614216
2583/3780 0.350 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5190190346506812
2584/3780 0.350 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6427809351989112
2585/3780 0.350 0.082 0.1 StandardScaler() 0 -> 0.50921608174797
2586/3780 0.350 0.082 0.1 MinMaxScaler() 0 -> 0.5777690634696815
2587/3780 0.350 0.082 0.31622776601683794 StandardScaler() 0 -> 0.550414370215437
2588/3780 0.350 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5444888947648457
2589/3780 0.350 0.082 1.0 StandardScaler() 0 -> 0.7520088606160233
2590/3780 0.350 0.082 1.0 MinMaxScaler() 0 -> 0.5173007533432795
2591/3780 0.350 0.104 scale StandardScaler() 0 -> 0.5030939564315693
2592/3780 0.350 0.104 scale MinMaxScaler() 0 -> 0.5037105063010285
2593/3780 0.350 0.104 auto StandardScaler() 0 -> 0.5030939564315693
2594/3780 0.350 0.104 auto MinMaxScaler() 0 -> 0.5725935527267456
2595/3780 0.350 0.104 0.01 StandardScaler() 0 -> 0.5448951418098987
2596/3780 0.350 0.104 0.01 MinMaxScaler() 0 -> 0.7331390608430137
2597/3780 0.350 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5141907943850399
2598/3780 0.350 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6214248917457498
2599/3780 0.350 0.104 0.1 StandardScaler() 0 -> 0.5038172623921914
2600/3780 0.350 0.104 0.1 MinMaxScaler() 0 -> 0.5695386453426616
2601/3780 0.350 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5370925376318111
2602/3780 0.350 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5399570399241896
2603/3780 0.350 0.104 1.0 StandardScaler() 0 -> 0.7349908721816223
2604/3780 0.350 0.104 1.0 MinMaxScaler() 0 -> 0.5129864601233699
2605/3780 0.350 0.132 scale StandardScaler() 0 -> 0.498744912589125
2606/3780 0.350 0.132 scale MinMaxScaler() 0 -> 0.49902090171023666
2607/3780 0.350 0.132 auto StandardScaler() 0 -> 0.498744912589125
2608/3780 0.350 0.132 auto MinMaxScaler() 0 -> 0.5661148632002883
2609/3780 0.350 0.132 0.01 StandardScaler() 0 -> 0.5395795696942056
2610/3780 0.350 0.132 0.01 MinMaxScaler() 0 -> 0.7124931908494565
2611/3780 0.350 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5088983629857924
2612/3780 0.350 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6052150577184842
2613/3780 0.350 0.132 0.1 StandardScaler() 0 -> 0.49875392532979057
2614/3780 0.350 0.132 0.1 MinMaxScaler() 0 -> 0.5637664665205419
2615/3780 0.350 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5261995874338089
2616/3780 0.350 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5354215801919819
2617/3780 0.350 0.132 1.0 StandardScaler() 0 -> 0.7139873704642435
2618/3780 0.350 0.132 1.0 MinMaxScaler() 0 -> 0.5085978925167005
2619/3780 0.350 0.168 scale StandardScaler() 0 -> 0.4945736860631483
2620/3780 0.350 0.168 scale MinMaxScaler() 0 -> 0.49516590576572234
2621/3780 0.350 0.168 auto StandardScaler() 0 -> 0.4945736860631484
2622/3780 0.350 0.168 auto MinMaxScaler() 0 -> 0.5618044262089111
2623/3780 0.350 0.168 0.01 StandardScaler() 0 -> 0.5348770881593925
2624/3780 0.350 0.168 0.01 MinMaxScaler() 0 -> 0.6888409421178435
2625/3780 0.350 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5055151712397269
2626/3780 0.350 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.5936132674266742
2627/3780 0.350 0.168 0.1 StandardScaler() 0 -> 0.49458725281906685
2628/3780 0.350 0.168 0.1 MinMaxScaler() 0 -> 0.5597753461387642
2629/3780 0.350 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5164734456458652
2630/3780 0.350 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5309644735837599
2631/3780 0.350 0.168 1.0 StandardScaler() 0 -> 0.6879115127722605
2632/3780 0.350 0.168 1.0 MinMaxScaler() 0 -> 0.5045750811656095
2633/3780 0.350 0.213 scale StandardScaler() 0 -> 0.49075788926013386
2634/3780 0.350 0.213 scale MinMaxScaler() 0 -> 0.49170118287641845
2635/3780 0.350 0.213 auto StandardScaler() 0 -> 0.4907578892601339
2636/3780 0.350 0.213 auto MinMaxScaler() 0 -> 0.5572286300025732
2637/3780 0.350 0.213 0.01 StandardScaler() 0 -> 0.5302755569614015
2638/3780 0.350 0.213 0.01 MinMaxScaler() 0 -> 0.662899358600249
2639/3780 0.350 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5012089435857757
2640/3780 0.350 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5848973602123403
2641/3780 0.350 0.213 0.1 StandardScaler() 0 -> 0.49047848203526767
2642/3780 0.350 0.213 0.1 MinMaxScaler() 0 -> 0.5551190564568325
2643/3780 0.350 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5072704955845653
2644/3780 0.350 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5270953950979065
2645/3780 0.350 0.213 1.0 StandardScaler() 0 -> 0.6577616514305226
2646/3780 0.350 0.213 1.0 MinMaxScaler() 0 -> 0.5004773824532339
2647/3780 0.350 0.270 scale StandardScaler() 0 -> 0.4873308067289172
2648/3780 0.350 0.270 scale MinMaxScaler() 0 -> 0.4890173516261018
2649/3780 0.350 0.270 auto StandardScaler() 0 -> 0.4873308067289172
2650/3780 0.350 0.270 auto MinMaxScaler() 0 -> 0.5536352166826007
2651/3780 0.350 0.270 0.01 StandardScaler() 0 -> 0.5259657324795213
2652/3780 0.350 0.270 0.01 MinMaxScaler() 0 -> 0.6376077713476067
2653/3780 0.350 0.270 0.03162277660168379 StandardScaler() 0 -> 0.49815336391950743
2654/3780 0.350 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5768155917205804
2655/3780 0.350 0.270 0.1 StandardScaler() 0 -> 0.487093197452466
2656/3780 0.350 0.270 0.1 MinMaxScaler() 0 -> 0.551944943357364
2657/3780 0.350 0.270 0.31622776601683794 StandardScaler() 0 -> 0.4988104216774823
2658/3780 0.350 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5237051024543526
2659/3780 0.350 0.270 1.0 StandardScaler() 0 -> 0.6258390429531717
2660/3780 0.350 0.270 1.0 MinMaxScaler() 0 -> 0.4978079058570808
2661/3780 0.350 0.342 scale StandardScaler() 0 -> 0.48420262801374814
2662/3780 0.350 0.342 scale MinMaxScaler() 0 -> 0.4859175741075194
2663/3780 0.350 0.342 auto StandardScaler() 0 -> 0.4842026280137483
2664/3780 0.350 0.342 auto MinMaxScaler() 0 -> 0.550231624965951
2665/3780 0.350 0.342 0.01 StandardScaler() 0 -> 0.5221255676664168
2666/3780 0.350 0.342 0.01 MinMaxScaler() 0 -> 0.6172998549727499
2667/3780 0.350 0.342 0.03162277660168379 StandardScaler() 0 -> 0.49445927450495036
2668/3780 0.350 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5699302042306045
2669/3780 0.350 0.342 0.1 StandardScaler() 0 -> 0.48341537528246437
2670/3780 0.350 0.342 0.1 MinMaxScaler() 0 -> 0.5484994721943366
2671/3780 0.350 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4908731419372209
2672/3780 0.350 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5204674772294577
2673/3780 0.350 0.342 1.0 StandardScaler() 0 -> 0.5934908493286923
2674/3780 0.350 0.342 1.0 MinMaxScaler() 0 -> 0.4947948042927924
2675/3780 0.350 0.434 scale StandardScaler() 0 -> 0.4812359021702433
2676/3780 0.350 0.434 scale MinMaxScaler() 0 -> 0.48349455020533466
2677/3780 0.350 0.434 auto StandardScaler() 0 -> 0.48123590217024326
2678/3780 0.350 0.434 auto MinMaxScaler() 0 -> 0.5473225689675124
2679/3780 0.350 0.434 0.01 StandardScaler() 0 -> 0.5180645497315463
2680/3780 0.350 0.434 0.01 MinMaxScaler() 0 -> 0.6028639355718077
2681/3780 0.350 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49151942878092286
2682/3780 0.350 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5653632367012699
2683/3780 0.350 0.434 0.1 StandardScaler() 0 -> 0.4804745580623366
2684/3780 0.350 0.434 0.1 MinMaxScaler() 0 -> 0.5452249079276825
2685/3780 0.350 0.434 0.31622776601683794 StandardScaler() 0 -> 0.48393206232034186
2686/3780 0.350 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5162556641336208
2687/3780 0.350 0.434 1.0 StandardScaler() 0 -> 0.5644526287628068
2688/3780 0.350 0.434 1.0 MinMaxScaler() 0 -> 0.4925346875823025
2689/3780 0.350 0.551 scale StandardScaler() 0 -> 0.4788085891098328
2690/3780 0.350 0.551 scale MinMaxScaler() 0 -> 0.48064765885590094
2691/3780 0.350 0.551 auto StandardScaler() 0 -> 0.47880858910983265
2692/3780 0.350 0.551 auto MinMaxScaler() 0 -> 0.5441173255571425
2693/3780 0.350 0.551 0.01 StandardScaler() 0 -> 0.5144430455261705
2694/3780 0.350 0.551 0.01 MinMaxScaler() 0 -> 0.5918094816779802
2695/3780 0.350 0.551 0.03162277660168379 StandardScaler() 0 -> 0.4899128295035677
2696/3780 0.350 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5613576050692541
2697/3780 0.350 0.551 0.1 StandardScaler() 0 -> 0.47814014145759004
2698/3780 0.350 0.551 0.1 MinMaxScaler() 0 -> 0.5420484729453182
2699/3780 0.350 0.551 0.31622776601683794 StandardScaler() 0 -> 0.477839240292905
2700/3780 0.350 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5124831848989873
2701/3780 0.350 0.551 1.0 StandardScaler() 0 -> 0.5417582060181861
2702/3780 0.350 0.551 1.0 MinMaxScaler() 0 -> 0.49050238177689187
2703/3780 0.350 0.700 scale StandardScaler() 0 -> 0.4767842692078146
2704/3780 0.350 0.700 scale MinMaxScaler() 0 -> 0.4783274410089409
2705/3780 0.350 0.700 auto StandardScaler() 0 -> 0.4767842692078144
2706/3780 0.350 0.700 auto MinMaxScaler() 0 -> 0.5409037417840074
2707/3780 0.350 0.700 0.01 StandardScaler() 0 -> 0.5110605713494497
2708/3780 0.350 0.700 0.01 MinMaxScaler() 0 -> 0.5835102563203644
2709/3780 0.350 0.700 0.03162277660168379 StandardScaler() 0 -> 0.48834460610596314
2710/3780 0.350 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5579185194994486
2711/3780 0.350 0.700 0.1 StandardScaler() 0 -> 0.4760935832193994
2712/3780 0.350 0.700 0.1 MinMaxScaler() 0 -> 0.5385713348950608
2713/3780 0.350 0.700 0.31622776601683794 StandardScaler() 0 -> 0.47271060651881297
2714/3780 0.350 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5091851515470226
2715/3780 0.350 0.700 1.0 StandardScaler() 0 -> 0.5268580025908157
2716/3780 0.350 0.700 1.0 MinMaxScaler() 0 -> 0.4887163733606275
2717/3780 0.350 0.888 scale StandardScaler() 0 -> 0.47508983303540386
2718/3780 0.350 0.888 scale MinMaxScaler() 0 -> 0.4760469487528316
2719/3780 0.350 0.888 auto StandardScaler() 0 -> 0.4750898330354039
2720/3780 0.350 0.888 auto MinMaxScaler() 0 -> 0.5375172218106532
2721/3780 0.350 0.888 0.01 StandardScaler() 0 -> 0.5077917685884785
2722/3780 0.350 0.888 0.01 MinMaxScaler() 0 -> 0.575650858919951
2723/3780 0.350 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4870169512775509
2724/3780 0.350 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5557819121948667
2725/3780 0.350 0.888 0.1 StandardScaler() 0 -> 0.4740827225792741
2726/3780 0.350 0.888 0.1 MinMaxScaler() 0 -> 0.5350476750420422
2727/3780 0.350 0.888 0.31622776601683794 StandardScaler() 0 -> 0.4693286737797642
2728/3780 0.350 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5064469669278796
2729/3780 0.350 0.888 1.0 StandardScaler() 0 -> 0.5193237595053688
2730/3780 0.350 0.888 1.0 MinMaxScaler() 0 -> 0.4869562110003504
2731/3780 0.350 1.126 scale StandardScaler() 0 -> 0.47296226028671695
2732/3780 0.350 1.126 scale MinMaxScaler() 0 -> 0.4739631612167832
2733/3780 0.350 1.126 auto StandardScaler() 0 -> 0.4729622602867171
2734/3780 0.350 1.126 auto MinMaxScaler() 0 -> 0.534189658494767
2735/3780 0.350 1.126 0.01 StandardScaler() 0 -> 0.5045451095382634
2736/3780 0.350 1.126 0.01 MinMaxScaler() 0 -> 0.569425479231403
2737/3780 0.350 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48551494798496786
2738/3780 0.350 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.553572109717602
2739/3780 0.350 1.126 0.1 StandardScaler() 0 -> 0.47144155257342774
2740/3780 0.350 1.126 0.1 MinMaxScaler() 0 -> 0.5321623542174375
2741/3780 0.350 1.126 0.31622776601683794 StandardScaler() 0 -> 0.467061593260984
2742/3780 0.350 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5038284151044702
2743/3780 0.350 1.126 1.0 StandardScaler() 0 -> 0.5140653731367811
2744/3780 0.350 1.126 1.0 MinMaxScaler() 0 -> 0.48482583058255996
2745/3780 0.350 1.429 scale StandardScaler() 0 -> 0.47077867895459596
2746/3780 0.350 1.429 scale MinMaxScaler() 0 -> 0.47308250265692003
2747/3780 0.350 1.429 auto StandardScaler() 0 -> 0.4707786789545958
2748/3780 0.350 1.429 auto MinMaxScaler() 0 -> 0.5314721344557798
2749/3780 0.350 1.429 0.01 StandardScaler() 0 -> 0.5014017686263682
2750/3780 0.350 1.429 0.01 MinMaxScaler() 0 -> 0.5654975319910936
2751/3780 0.350 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48409087263383555
2752/3780 0.350 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5515653977499339
2753/3780 0.350 1.429 0.1 StandardScaler() 0 -> 0.4695697694655405
2754/3780 0.350 1.429 0.1 MinMaxScaler() 0 -> 0.5291869879216583
2755/3780 0.350 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4658897425759378
2756/3780 0.350 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5011066140662073
2757/3780 0.350 1.429 1.0 StandardScaler() 0 -> 0.51001099315551
2758/3780 0.350 1.429 1.0 MinMaxScaler() 0 -> 0.4831971684635421
2759/3780 0.350 1.814 scale StandardScaler() 0 -> 0.4695487859606864
2760/3780 0.350 1.814 scale MinMaxScaler() 0 -> 0.47271135769730854
2761/3780 0.350 1.814 auto StandardScaler() 0 -> 0.4695487859606868
2762/3780 0.350 1.814 auto MinMaxScaler() 0 -> 0.5286208093347646
2763/3780 0.350 1.814 0.01 StandardScaler() 0 -> 0.4987270759361664
2764/3780 0.350 1.814 0.01 MinMaxScaler() 0 -> 0.5617245101933471
2765/3780 0.350 1.814 0.03162277660168379 StandardScaler() 0 -> 0.4829324776755071
2766/3780 0.350 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5493798847252822
2767/3780 0.350 1.814 0.1 StandardScaler() 0 -> 0.46879068988009304
2768/3780 0.350 1.814 0.1 MinMaxScaler() 0 -> 0.5260964188709362
2769/3780 0.350 1.814 0.31622776601683794 StandardScaler() 0 -> 0.46706154018318924
2770/3780 0.350 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.49816312288723624
2771/3780 0.350 1.814 1.0 StandardScaler() 0 -> 0.508442122073269
2772/3780 0.350 1.814 1.0 MinMaxScaler() 0 -> 0.48178136237356206
2773/3780 0.350 2.302 scale StandardScaler() 0 -> 0.46911304537577075
2774/3780 0.350 2.302 scale MinMaxScaler() 0 -> 0.4722587907508704
2775/3780 0.350 2.302 auto StandardScaler() 0 -> 0.46911304537577075
2776/3780 0.350 2.302 auto MinMaxScaler() 0 -> 0.5255878091399454
2777/3780 0.350 2.302 0.01 StandardScaler() 0 -> 0.49656228550943965
2778/3780 0.350 2.302 0.01 MinMaxScaler() 0 -> 0.5589104036612048
2779/3780 0.350 2.302 0.03162277660168379 StandardScaler() 0 -> 0.48193164194125765
2780/3780 0.350 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5476527903426462
2781/3780 0.350 2.302 0.1 StandardScaler() 0 -> 0.46874608995591566
2782/3780 0.350 2.302 0.1 MinMaxScaler() 0 -> 0.5230912934271015
2783/3780 0.350 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4694577215422999
2784/3780 0.350 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.49615519445452705
2785/3780 0.350 2.302 1.0 StandardScaler() 0 -> 0.5081590728829629
2786/3780 0.350 2.302 1.0 MinMaxScaler() 0 -> 0.48029772646703045
2787/3780 0.350 2.921 scale StandardScaler() 0 -> 0.46951953344880565
2788/3780 0.350 2.921 scale MinMaxScaler() 0 -> 0.47194196605998245
2789/3780 0.350 2.921 auto StandardScaler() 0 -> 0.4695195334488071
2790/3780 0.350 2.921 auto MinMaxScaler() 0 -> 0.5222882497884779
2791/3780 0.350 2.921 0.01 StandardScaler() 0 -> 0.49563481723169334
2792/3780 0.350 2.921 0.01 MinMaxScaler() 0 -> 0.557284346468589
2793/3780 0.350 2.921 0.03162277660168379 StandardScaler() 0 -> 0.4811150024053968
2794/3780 0.350 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5456801962910366
2795/3780 0.350 2.921 0.1 StandardScaler() 0 -> 0.46992379538851187
2796/3780 0.350 2.921 0.1 MinMaxScaler() 0 -> 0.5194669139249966
2797/3780 0.350 2.921 0.31622776601683794 StandardScaler() 0 -> 0.4737001906615501
2798/3780 0.350 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49430584983160336
2799/3780 0.350 2.921 1.0 StandardScaler() 0 -> 0.5080762046573595
2800/3780 0.350 2.921 1.0 MinMaxScaler() 0 -> 0.4792894863262054
2801/3780 0.350 3.707 scale StandardScaler() 0 -> 0.47100326744940596
2802/3780 0.350 3.707 scale MinMaxScaler() 0 -> 0.4724494121215601
2803/3780 0.350 3.707 auto StandardScaler() 0 -> 0.471003267449406
2804/3780 0.350 3.707 auto MinMaxScaler() 0 -> 0.5188117125474173
2805/3780 0.350 3.707 0.01 StandardScaler() 0 -> 0.4939904476872273
2806/3780 0.350 3.707 0.01 MinMaxScaler() 0 -> 0.5557395008742133
2807/3780 0.350 3.707 0.03162277660168379 StandardScaler() 0 -> 0.48010020328927366
2808/3780 0.350 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5431876497743855
2809/3780 0.350 3.707 0.1 StandardScaler() 0 -> 0.4711785370955864
2810/3780 0.350 3.707 0.1 MinMaxScaler() 0 -> 0.5162233314310026
2811/3780 0.350 3.707 0.31622776601683794 StandardScaler() 0 -> 0.47837548580029976
2812/3780 0.350 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4927305315033316
2813/3780 0.350 3.707 1.0 StandardScaler() 0 -> 0.508058454161724
2814/3780 0.350 3.707 1.0 MinMaxScaler() 0 -> 0.4777247360925834
2815/3780 0.350 4.703 scale StandardScaler() 0 -> 0.4727713791647488
2816/3780 0.350 4.703 scale MinMaxScaler() 0 -> 0.47336014171836976
2817/3780 0.350 4.703 auto StandardScaler() 0 -> 0.47277137916474826
2818/3780 0.350 4.703 auto MinMaxScaler() 0 -> 0.5155621756438379
2819/3780 0.350 4.703 0.01 StandardScaler() 0 -> 0.49304717622152944
2820/3780 0.350 4.703 0.01 MinMaxScaler() 0 -> 0.5541565912051668
2821/3780 0.350 4.703 0.03162277660168379 StandardScaler() 0 -> 0.4796523731292202
2822/3780 0.350 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5403926394094335
2823/3780 0.350 4.703 0.1 StandardScaler() 0 -> 0.47290880971189414
2824/3780 0.350 4.703 0.1 MinMaxScaler() 0 -> 0.5131552110561837
2825/3780 0.350 4.703 0.31622776601683794 StandardScaler() 0 -> 0.4831148659353571
2826/3780 0.350 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.4920585685600034
2827/3780 0.350 4.703 1.0 StandardScaler() 0 -> 0.508058337123614
2828/3780 0.350 4.703 1.0 MinMaxScaler() 0 -> 0.4768115157547965
2829/3780 0.350 5.968 scale StandardScaler() 0 -> 0.47488279026155
2830/3780 0.350 5.968 scale MinMaxScaler() 0 -> 0.47495911604647345
2831/3780 0.350 5.968 auto StandardScaler() 0 -> 0.47488279026154984
2832/3780 0.350 5.968 auto MinMaxScaler() 0 -> 0.5127650181962113
2833/3780 0.350 5.968 0.01 StandardScaler() 0 -> 0.49233670254705125
2834/3780 0.350 5.968 0.01 MinMaxScaler() 0 -> 0.5528463184623486
2835/3780 0.350 5.968 0.03162277660168379 StandardScaler() 0 -> 0.4795995778413437
2836/3780 0.350 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.537986818086571
2837/3780 0.350 5.968 0.1 StandardScaler() 0 -> 0.4765766666858491
2838/3780 0.350 5.968 0.1 MinMaxScaler() 0 -> 0.5104724678031974
2839/3780 0.350 5.968 0.31622776601683794 StandardScaler() 0 -> 0.48754612955877485
2840/3780 0.350 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.4915652172941056
2841/3780 0.350 5.968 1.0 StandardScaler() 0 -> 0.5080589534805994
2842/3780 0.350 5.968 1.0 MinMaxScaler() 0 -> 0.4765037259222417
2843/3780 0.350 7.574 scale StandardScaler() 0 -> 0.47876188450152113
2844/3780 0.350 7.574 scale MinMaxScaler() 0 -> 0.47764128293559777
2845/3780 0.350 7.574 auto StandardScaler() 0 -> 0.4787618845015205
2846/3780 0.350 7.574 auto MinMaxScaler() 0 -> 0.5100652955005339
2847/3780 0.350 7.574 0.01 StandardScaler() 0 -> 0.49151659218746707
2848/3780 0.350 7.574 0.01 MinMaxScaler() 0 -> 0.5517294631551718
2849/3780 0.350 7.574 0.03162277660168379 StandardScaler() 0 -> 0.47889514205234773
2850/3780 0.350 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5355707360709788
2851/3780 0.350 7.574 0.1 StandardScaler() 0 -> 0.48193116973633937
2852/3780 0.350 7.574 0.1 MinMaxScaler() 0 -> 0.5082394613258386
2853/3780 0.350 7.574 0.31622776601683794 StandardScaler() 0 -> 0.49154217778298653
2854/3780 0.350 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.4909595746518545
2855/3780 0.350 7.574 1.0 StandardScaler() 0 -> 0.5080589534805994
2856/3780 0.350 7.574 1.0 MinMaxScaler() 0 -> 0.47630811083425195
2857/3780 0.350 9.611 scale StandardScaler() 0 -> 0.4842329621303922
2858/3780 0.350 9.611 scale MinMaxScaler() 0 -> 0.4803907781230868
2859/3780 0.350 9.611 auto StandardScaler() 0 -> 0.48423296213039174
2860/3780 0.350 9.611 auto MinMaxScaler() 0 -> 0.5077185887902639
2861/3780 0.350 9.611 0.01 StandardScaler() 0 -> 0.490811724442703
2862/3780 0.350 9.611 0.01 MinMaxScaler() 0 -> 0.5506274700404878
2863/3780 0.350 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4778319175705394
2864/3780 0.350 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5332983846083001
2865/3780 0.350 9.611 0.1 StandardScaler() 0 -> 0.490023946002155
2866/3780 0.350 9.611 0.1 MinMaxScaler() 0 -> 0.5056491672309078
2867/3780 0.350 9.611 0.31622776601683794 StandardScaler() 0 -> 0.4952854012572676
2868/3780 0.350 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4900246612443337
2869/3780 0.350 9.611 1.0 StandardScaler() 0 -> 0.5080589534805994
2870/3780 0.350 9.611 1.0 MinMaxScaler() 0 -> 0.4761712592678892
2871/3780 0.350 12.196 scale StandardScaler() 0 -> 0.4927921044223553
2872/3780 0.350 12.196 scale MinMaxScaler() 0 -> 0.4840687819028404
2873/3780 0.350 12.196 auto StandardScaler() 0 -> 0.49279210442235355
2874/3780 0.350 12.196 auto MinMaxScaler() 0 -> 0.5051952121475657
2875/3780 0.350 12.196 0.01 StandardScaler() 0 -> 0.4899416735826428
2876/3780 0.350 12.196 0.01 MinMaxScaler() 0 -> 0.5494276383473631
2877/3780 0.350 12.196 0.03162277660168379 StandardScaler() 0 -> 0.47742984106458763
2878/3780 0.350 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5304173760879375
2879/3780 0.350 12.196 0.1 StandardScaler() 0 -> 0.49825948247681606
2880/3780 0.350 12.196 0.1 MinMaxScaler() 0 -> 0.5036479653104715
2881/3780 0.350 12.196 0.31622776601683794 StandardScaler() 0 -> 0.49780856150728536
2882/3780 0.350 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4891955295810877
2883/3780 0.350 12.196 1.0 StandardScaler() 0 -> 0.5080589534805994
2884/3780 0.350 12.196 1.0 MinMaxScaler() 0 -> 0.4765135884085589
2885/3780 0.350 15.476 scale StandardScaler() 0 -> 0.5023715382194966
2886/3780 0.350 15.476 scale MinMaxScaler() 0 -> 0.4899385009900663
2887/3780 0.350 15.476 auto StandardScaler() 0 -> 0.5023715382195014
2888/3780 0.350 15.476 auto MinMaxScaler() 0 -> 0.5031044145653891
2889/3780 0.350 15.476 0.01 StandardScaler() 0 -> 0.4891474275692287
2890/3780 0.350 15.476 0.01 MinMaxScaler() 0 -> 0.5481393753472695
2891/3780 0.350 15.476 0.03162277660168379 StandardScaler() 0 -> 0.4783126352838882
2892/3780 0.350 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5273993124879058
2893/3780 0.350 15.476 0.1 StandardScaler() 0 -> 0.509232142853744
2894/3780 0.350 15.476 0.1 MinMaxScaler() 0 -> 0.5011681157827043
2895/3780 0.350 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5000102003147513
2896/3780 0.350 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.48818154338100905
2897/3780 0.350 15.476 1.0 StandardScaler() 0 -> 0.5080589534805994
2898/3780 0.350 15.476 1.0 MinMaxScaler() 0 -> 0.4773943916267389
2899/3780 0.350 19.638 scale StandardScaler() 0 -> 0.5135539925488356
2900/3780 0.350 19.638 scale MinMaxScaler() 0 -> 0.49773758204911195
2901/3780 0.350 19.638 auto StandardScaler() 0 -> 0.5135539925488337
2902/3780 0.350 19.638 auto MinMaxScaler() 0 -> 0.5009407856771265
2903/3780 0.350 19.638 0.01 StandardScaler() 0 -> 0.48841517324477607
2904/3780 0.350 19.638 0.01 MinMaxScaler() 0 -> 0.5466266859688922
2905/3780 0.350 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4798494176759191
2906/3780 0.350 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5247125411394472
2907/3780 0.350 19.638 0.1 StandardScaler() 0 -> 0.5229304226564903
2908/3780 0.350 19.638 0.1 MinMaxScaler() 0 -> 0.49904043354944033
2909/3780 0.350 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5016427868034175
2910/3780 0.350 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.4875699569429166
2911/3780 0.350 19.638 1.0 StandardScaler() 0 -> 0.5080589534805994
2912/3780 0.350 19.638 1.0 MinMaxScaler() 0 -> 0.47867457379806705
2913/3780 0.350 24.920 scale StandardScaler() 0 -> 0.5284888137053309
2914/3780 0.350 24.920 scale MinMaxScaler() 0 -> 0.5072315350035735
2915/3780 0.350 24.920 auto StandardScaler() 0 -> 0.5284888137053232
2916/3780 0.350 24.920 auto MinMaxScaler() 0 -> 0.49883308719640745
2917/3780 0.350 24.920 0.01 StandardScaler() 0 -> 0.48764021043155886
2918/3780 0.350 24.920 0.01 MinMaxScaler() 0 -> 0.5451416529246774
2919/3780 0.350 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4815759342124155
2920/3780 0.350 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5214116740382545
2921/3780 0.350 24.920 0.1 StandardScaler() 0 -> 0.5365673785158669
2922/3780 0.350 24.920 0.1 MinMaxScaler() 0 -> 0.4973128841615497
2923/3780 0.350 24.920 0.31622776601683794 StandardScaler() 0 -> 0.502000195118326
2924/3780 0.350 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.48626270251354836
2925/3780 0.350 24.920 1.0 StandardScaler() 0 -> 0.5080589534805994
2926/3780 0.350 24.920 1.0 MinMaxScaler() 0 -> 0.4800230231507386
2927/3780 0.350 31.623 scale StandardScaler() 0 -> 0.5435223745110555
2928/3780 0.350 31.623 scale MinMaxScaler() 0 -> 0.517684611681737
2929/3780 0.350 31.623 auto StandardScaler() 0 -> 0.543522374511058
2930/3780 0.350 31.623 auto MinMaxScaler() 0 -> 0.49720406213649554
2931/3780 0.350 31.623 0.01 StandardScaler() 0 -> 0.48691261519619644
2932/3780 0.350 31.623 0.01 MinMaxScaler() 0 -> 0.5434704707962669
2933/3780 0.350 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4830040150574089
2934/3780 0.350 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.517880280727327
2935/3780 0.350 31.623 0.1 StandardScaler() 0 -> 0.5535284120671519
2936/3780 0.350 31.623 0.1 MinMaxScaler() 0 -> 0.49603812573609396
2937/3780 0.350 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5022568815784573
2938/3780 0.350 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.48505631491865603
2939/3780 0.350 31.623 1.0 StandardScaler() 0 -> 0.5080589534805994
2940/3780 0.350 31.623 1.0 MinMaxScaler() 0 -> 0.48245105786920967
2941/3780 0.400 0.032 scale StandardScaler() 0 -> 0.5417348681242031
2942/3780 0.400 0.032 scale MinMaxScaler() 0 -> 0.5370060659616941
2943/3780 0.400 0.032 auto StandardScaler() 0 -> 0.5417348681242031
2944/3780 0.400 0.032 auto MinMaxScaler() 0 -> 0.6475939493873989
2945/3780 0.400 0.032 0.01 StandardScaler() 0 -> 0.581873283256096
2946/3780 0.400 0.032 0.01 MinMaxScaler() 0 -> 0.8213766959077392
2947/3780 0.400 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5478079719280933
2948/3780 0.400 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.7598602997195522
2949/3780 0.400 0.032 0.1 StandardScaler() 0 -> 0.5428785411404848
2950/3780 0.400 0.032 0.1 MinMaxScaler() 0 -> 0.637029655201282
2951/3780 0.400 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6219385891786092
2952/3780 0.400 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5732590240568417
2953/3780 0.400 0.032 1.0 StandardScaler() 0 -> 0.8236325892790992
2954/3780 0.400 0.032 1.0 MinMaxScaler() 0 -> 0.5429484027723726
2955/3780 0.400 0.040 scale StandardScaler() 0 -> 0.5337245926377419
2956/3780 0.400 0.040 scale MinMaxScaler() 0 -> 0.5312797253652944
2957/3780 0.400 0.040 auto StandardScaler() 0 -> 0.5337245926377419
2958/3780 0.400 0.040 auto MinMaxScaler() 0 -> 0.6210057570933828
2959/3780 0.400 0.040 0.01 StandardScaler() 0 -> 0.5736865861794029
2960/3780 0.400 0.040 0.01 MinMaxScaler() 0 -> 0.8129981691226785
2961/3780 0.400 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5417121355813762
2962/3780 0.400 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7382250407591773
2963/3780 0.400 0.040 0.1 StandardScaler() 0 -> 0.5348181233670221
2964/3780 0.400 0.040 0.1 MinMaxScaler() 0 -> 0.6121301911010145
2965/3780 0.400 0.040 0.31622776601683794 StandardScaler() 0 -> 0.6046238079170788
2966/3780 0.400 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5652613531934959
2967/3780 0.400 0.040 1.0 StandardScaler() 0 -> 0.8160525325134449
2968/3780 0.400 0.040 1.0 MinMaxScaler() 0 -> 0.5379203953148218
2969/3780 0.400 0.051 scale StandardScaler() 0 -> 0.5267008518859969
2970/3780 0.400 0.051 scale MinMaxScaler() 0 -> 0.5261103875778492
2971/3780 0.400 0.051 auto StandardScaler() 0 -> 0.5267008518859969
2972/3780 0.400 0.051 auto MinMaxScaler() 0 -> 0.6014070772452453
2973/3780 0.400 0.051 0.01 StandardScaler() 0 -> 0.5658640873708746
2974/3780 0.400 0.051 0.01 MinMaxScaler() 0 -> 0.8025989057553824
2975/3780 0.400 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5356783626178911
2976/3780 0.400 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7131506629916439
2977/3780 0.400 0.051 0.1 StandardScaler() 0 -> 0.5270182646134587
2978/3780 0.400 0.051 0.1 MinMaxScaler() 0 -> 0.5958439972785499
2979/3780 0.400 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5879041814149022
2980/3780 0.400 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.5587385843170211
2981/3780 0.400 0.051 1.0 StandardScaler() 0 -> 0.806679387596645
2982/3780 0.400 0.051 1.0 MinMaxScaler() 0 -> 0.5320111101496882
2983/3780 0.400 0.065 scale StandardScaler() 0 -> 0.5201308430772483
2984/3780 0.400 0.065 scale MinMaxScaler() 0 -> 0.5197750723134164
2985/3780 0.400 0.065 auto StandardScaler() 0 -> 0.5201308430772483
2986/3780 0.400 0.065 auto MinMaxScaler() 0 -> 0.5904792759567128
2987/3780 0.400 0.065 0.01 StandardScaler() 0 -> 0.5588862042615987
2988/3780 0.400 0.065 0.01 MinMaxScaler() 0 -> 0.7897805012464697
2989/3780 0.400 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5293191788017105
2990/3780 0.400 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.6853646263037497
2991/3780 0.400 0.065 0.1 StandardScaler() 0 -> 0.5205092834923937
2992/3780 0.400 0.065 0.1 MinMaxScaler() 0 -> 0.5870119203555703
2993/3780 0.400 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5715054344079241
2994/3780 0.400 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.5532442596306376
2995/3780 0.400 0.065 1.0 StandardScaler() 0 -> 0.7950032257894232
2996/3780 0.400 0.065 1.0 MinMaxScaler() 0 -> 0.5268381108506868
2997/3780 0.400 0.082 scale StandardScaler() 0 -> 0.5143632133464473
2998/3780 0.400 0.082 scale MinMaxScaler() 0 -> 0.5144522371037206
2999/3780 0.400 0.082 auto StandardScaler() 0 -> 0.5143632133464472
3000/3780 0.400 0.082 auto MinMaxScaler() 0 -> 0.5827873598788526
3001/3780 0.400 0.082 0.01 StandardScaler() 0 -> 0.5534950426863142
3002/3780 0.400 0.082 0.01 MinMaxScaler() 0 -> 0.7741150979626927
3003/3780 0.400 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5238548223801088
3004/3780 0.400 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6559115558463979
3005/3780 0.400 0.082 0.1 StandardScaler() 0 -> 0.514588028012363
3006/3780 0.400 0.082 0.1 MinMaxScaler() 0 -> 0.5790556183928253
3007/3780 0.400 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5563963119513129
3008/3780 0.400 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5485562918660166
3009/3780 0.400 0.082 1.0 StandardScaler() 0 -> 0.7801926249247196
3010/3780 0.400 0.082 1.0 MinMaxScaler() 0 -> 0.5217177043457567
3011/3780 0.400 0.104 scale StandardScaler() 0 -> 0.5087236720093002
3012/3780 0.400 0.104 scale MinMaxScaler() 0 -> 0.5094314995733907
3013/3780 0.400 0.104 auto StandardScaler() 0 -> 0.5087236720093004
3014/3780 0.400 0.104 auto MinMaxScaler() 0 -> 0.5749438497179288
3015/3780 0.400 0.104 0.01 StandardScaler() 0 -> 0.5480294400604001
3016/3780 0.400 0.104 0.01 MinMaxScaler() 0 -> 0.7551977854304687
3017/3780 0.400 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5189572053455077
3018/3780 0.400 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6281849793143305
3019/3780 0.400 0.104 0.1 StandardScaler() 0 -> 0.5091649806692891
3020/3780 0.400 0.104 0.1 MinMaxScaler() 0 -> 0.5724850444752624
3021/3780 0.400 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5436726051110093
3022/3780 0.400 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5435740252088351
3023/3780 0.400 0.104 1.0 StandardScaler() 0 -> 0.7607929276369673
3024/3780 0.400 0.104 1.0 MinMaxScaler() 0 -> 0.5174738980407328
3025/3780 0.400 0.132 scale StandardScaler() 0 -> 0.5030918122317974
3026/3780 0.400 0.132 scale MinMaxScaler() 0 -> 0.504746910690706
3027/3780 0.400 0.132 auto StandardScaler() 0 -> 0.5030918122317973
3028/3780 0.400 0.132 auto MinMaxScaler() 0 -> 0.5692377377679888
3029/3780 0.400 0.132 0.01 StandardScaler() 0 -> 0.5431444351273748
3030/3780 0.400 0.132 0.01 MinMaxScaler() 0 -> 0.7327306467748471
3031/3780 0.400 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5138320836161911
3032/3780 0.400 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6061711207143669
3033/3780 0.400 0.132 0.1 StandardScaler() 0 -> 0.5031543408767091
3034/3780 0.400 0.132 0.1 MinMaxScaler() 0 -> 0.5668118774384848
3035/3780 0.400 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5324128304749546
3036/3780 0.400 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5396108846877797
3037/3780 0.400 0.132 1.0 StandardScaler() 0 -> 0.7350113201811442
3038/3780 0.400 0.132 1.0 MinMaxScaler() 0 -> 0.5136585545912687
3039/3780 0.400 0.168 scale StandardScaler() 0 -> 0.49827301716284184
3040/3780 0.400 0.168 scale MinMaxScaler() 0 -> 0.5001014162847675
3041/3780 0.400 0.168 auto StandardScaler() 0 -> 0.49827301716284195
3042/3780 0.400 0.168 auto MinMaxScaler() 0 -> 0.5640141189147504
3043/3780 0.400 0.168 0.01 StandardScaler() 0 -> 0.5388036529286124
3044/3780 0.400 0.168 0.01 MinMaxScaler() 0 -> 0.7069708368378683
3045/3780 0.400 0.168 0.03162277660168379 StandardScaler() 0 -> 0.509737997357936
3046/3780 0.400 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.5940867670710918
3047/3780 0.400 0.168 0.1 StandardScaler() 0 -> 0.49820292346390876
3048/3780 0.400 0.168 0.1 MinMaxScaler() 0 -> 0.5620003398532087
3049/3780 0.400 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5220524923936584
3050/3780 0.400 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5354172512991435
3051/3780 0.400 0.168 1.0 StandardScaler() 0 -> 0.7016941625003478
3052/3780 0.400 0.168 1.0 MinMaxScaler() 0 -> 0.5093628801199975
3053/3780 0.400 0.213 scale StandardScaler() 0 -> 0.494011221254413
3054/3780 0.400 0.213 scale MinMaxScaler() 0 -> 0.49596722097347407
3055/3780 0.400 0.213 auto StandardScaler() 0 -> 0.49401122125441294
3056/3780 0.400 0.213 auto MinMaxScaler() 0 -> 0.5596741604621274
3057/3780 0.400 0.213 0.01 StandardScaler() 0 -> 0.5336959537838143
3058/3780 0.400 0.213 0.01 MinMaxScaler() 0 -> 0.6790552508479121
3059/3780 0.400 0.213 0.03162277660168379 StandardScaler() 0 -> 0.5061384999265526
3060/3780 0.400 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5861406709003388
3061/3780 0.400 0.213 0.1 StandardScaler() 0 -> 0.49390802767560044
3062/3780 0.400 0.213 0.1 MinMaxScaler() 0 -> 0.5576382898341596
3063/3780 0.400 0.213 0.31622776601683794 StandardScaler() 0 -> 0.512948095070345
3064/3780 0.400 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5305728114242041
3065/3780 0.400 0.213 1.0 StandardScaler() 0 -> 0.6631525338109469
3066/3780 0.400 0.213 1.0 MinMaxScaler() 0 -> 0.5059255147386342
3067/3780 0.400 0.270 scale StandardScaler() 0 -> 0.4909650652217312
3068/3780 0.400 0.270 scale MinMaxScaler() 0 -> 0.49209745002280575
3069/3780 0.400 0.270 auto StandardScaler() 0 -> 0.4909650652217313
3070/3780 0.400 0.270 auto MinMaxScaler() 0 -> 0.5559041860113079
3071/3780 0.400 0.270 0.01 StandardScaler() 0 -> 0.5291803458185429
3072/3780 0.400 0.270 0.01 MinMaxScaler() 0 -> 0.6496845430736249
3073/3780 0.400 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5014958429527155
3074/3780 0.400 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5784651273783412
3075/3780 0.400 0.270 0.1 StandardScaler() 0 -> 0.4910418833951178
3076/3780 0.400 0.270 0.1 MinMaxScaler() 0 -> 0.5541989594218824
3077/3780 0.400 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5044009120838527
3078/3780 0.400 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5265533731574995
3079/3780 0.400 0.270 1.0 StandardScaler() 0 -> 0.625563948544136
3080/3780 0.400 0.270 1.0 MinMaxScaler() 0 -> 0.5024887974727145
3081/3780 0.400 0.342 scale StandardScaler() 0 -> 0.48799612521050584
3082/3780 0.400 0.342 scale MinMaxScaler() 0 -> 0.4890141940387001
3083/3780 0.400 0.342 auto StandardScaler() 0 -> 0.4879961252105059
3084/3780 0.400 0.342 auto MinMaxScaler() 0 -> 0.552415524104167
3085/3780 0.400 0.342 0.01 StandardScaler() 0 -> 0.5244925891736525
3086/3780 0.400 0.342 0.01 MinMaxScaler() 0 -> 0.6234823601948883
3087/3780 0.400 0.342 0.03162277660168379 StandardScaler() 0 -> 0.4979935966838442
3088/3780 0.400 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5724501323455945
3089/3780 0.400 0.342 0.1 StandardScaler() 0 -> 0.4876844762980357
3090/3780 0.400 0.342 0.1 MinMaxScaler() 0 -> 0.5502782027447526
3091/3780 0.400 0.342 0.31622776601683794 StandardScaler() 0 -> 0.4964469995755947
3092/3780 0.400 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5222537034828229
3093/3780 0.400 0.342 1.0 StandardScaler() 0 -> 0.591776641783705
3094/3780 0.400 0.342 1.0 MinMaxScaler() 0 -> 0.49909311644188703
3095/3780 0.400 0.434 scale StandardScaler() 0 -> 0.48523668652971647
3096/3780 0.400 0.434 scale MinMaxScaler() 0 -> 0.48600649031451787
3097/3780 0.400 0.434 auto StandardScaler() 0 -> 0.48523668652971635
3098/3780 0.400 0.434 auto MinMaxScaler() 0 -> 0.5487230772286869
3099/3780 0.400 0.434 0.01 StandardScaler() 0 -> 0.5208572494399182
3100/3780 0.400 0.434 0.01 MinMaxScaler() 0 -> 0.6034109754435261
3101/3780 0.400 0.434 0.03162277660168379 StandardScaler() 0 -> 0.49554286504916645
3102/3780 0.400 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.5678561195289135
3103/3780 0.400 0.434 0.1 StandardScaler() 0 -> 0.48508805576954633
3104/3780 0.400 0.434 0.1 MinMaxScaler() 0 -> 0.5470427892591695
3105/3780 0.400 0.434 0.31622776601683794 StandardScaler() 0 -> 0.48891334601908376
3106/3780 0.400 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5185413657592646
3107/3780 0.400 0.434 1.0 StandardScaler() 0 -> 0.5646041786473788
3108/3780 0.400 0.434 1.0 MinMaxScaler() 0 -> 0.4958384823655755
3109/3780 0.400 0.551 scale StandardScaler() 0 -> 0.4830624008774733
3110/3780 0.400 0.551 scale MinMaxScaler() 0 -> 0.4835618695177663
3111/3780 0.400 0.551 auto StandardScaler() 0 -> 0.4830624008774735
3112/3780 0.400 0.551 auto MinMaxScaler() 0 -> 0.5456661746676906
3113/3780 0.400 0.551 0.01 StandardScaler() 0 -> 0.5170698393074645
3114/3780 0.400 0.551 0.01 MinMaxScaler() 0 -> 0.5925300770879938
3115/3780 0.400 0.551 0.03162277660168379 StandardScaler() 0 -> 0.49328042499747865
3116/3780 0.400 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5638738330727576
3117/3780 0.400 0.551 0.1 StandardScaler() 0 -> 0.48256536229966834
3118/3780 0.400 0.551 0.1 MinMaxScaler() 0 -> 0.5434627229855735
3119/3780 0.400 0.551 0.31622776601683794 StandardScaler() 0 -> 0.4823673782628632
3120/3780 0.400 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.5148652430419317
3121/3780 0.400 0.551 1.0 StandardScaler() 0 -> 0.5446603234054801
3122/3780 0.400 0.551 1.0 MinMaxScaler() 0 -> 0.49340524209488174
3123/3780 0.400 0.700 scale StandardScaler() 0 -> 0.48066908988849244
3124/3780 0.400 0.700 scale MinMaxScaler() 0 -> 0.48094134034246405
3125/3780 0.400 0.700 auto StandardScaler() 0 -> 0.4806690898884924
3126/3780 0.400 0.700 auto MinMaxScaler() 0 -> 0.5426613958151362
3127/3780 0.400 0.700 0.01 StandardScaler() 0 -> 0.5133019939056495
3128/3780 0.400 0.700 0.01 MinMaxScaler() 0 -> 0.5848631371379541
3129/3780 0.400 0.700 0.03162277660168379 StandardScaler() 0 -> 0.4910117146249175
3130/3780 0.400 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5607820571881922
3131/3780 0.400 0.700 0.1 StandardScaler() 0 -> 0.4795266581642923
3132/3780 0.400 0.700 0.1 MinMaxScaler() 0 -> 0.5401649665714888
3133/3780 0.400 0.700 0.31622776601683794 StandardScaler() 0 -> 0.476997215231028
3134/3780 0.400 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5117972208282345
3135/3780 0.400 0.700 1.0 StandardScaler() 0 -> 0.5328793679798695
3136/3780 0.400 0.700 1.0 MinMaxScaler() 0 -> 0.49138176192703725
3137/3780 0.400 0.888 scale StandardScaler() 0 -> 0.4777500029180041
3138/3780 0.400 0.888 scale MinMaxScaler() 0 -> 0.47891550899731766
3139/3780 0.400 0.888 auto StandardScaler() 0 -> 0.477750002918004
3140/3780 0.400 0.888 auto MinMaxScaler() 0 -> 0.5391298931534565
3141/3780 0.400 0.888 0.01 StandardScaler() 0 -> 0.5088570435405795
3142/3780 0.400 0.888 0.01 MinMaxScaler() 0 -> 0.5777641756915767
3143/3780 0.400 0.888 0.03162277660168379 StandardScaler() 0 -> 0.48881157773083106
3144/3780 0.400 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5576754815231237
3145/3780 0.400 0.888 0.1 StandardScaler() 0 -> 0.47623279159703547
3146/3780 0.400 0.888 0.1 MinMaxScaler() 0 -> 0.5370763936464894
3147/3780 0.400 0.888 0.31622776601683794 StandardScaler() 0 -> 0.4734836065085777
3148/3780 0.400 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5081035309280103
3149/3780 0.400 0.888 1.0 StandardScaler() 0 -> 0.526401180850836
3150/3780 0.400 0.888 1.0 MinMaxScaler() 0 -> 0.4896454299639155
3151/3780 0.400 1.126 scale StandardScaler() 0 -> 0.4750256062436031
3152/3780 0.400 1.126 scale MinMaxScaler() 0 -> 0.4769259402736279
3153/3780 0.400 1.126 auto StandardScaler() 0 -> 0.47502560624360335
3154/3780 0.400 1.126 auto MinMaxScaler() 0 -> 0.5364853010582277
3155/3780 0.400 1.126 0.01 StandardScaler() 0 -> 0.504792939451162
3156/3780 0.400 1.126 0.01 MinMaxScaler() 0 -> 0.5727617352478814
3157/3780 0.400 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48743221846641555
3158/3780 0.400 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5551747853930892
3159/3780 0.400 1.126 0.1 StandardScaler() 0 -> 0.4735593619582416
3160/3780 0.400 1.126 0.1 MinMaxScaler() 0 -> 0.5343643393699312
3161/3780 0.400 1.126 0.31622776601683794 StandardScaler() 0 -> 0.4708473306480491
3162/3780 0.400 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5051890996048714
3163/3780 0.400 1.126 1.0 StandardScaler() 0 -> 0.5208868770717522
3164/3780 0.400 1.126 1.0 MinMaxScaler() 0 -> 0.4873786448634214
3165/3780 0.400 1.429 scale StandardScaler() 0 -> 0.4727170174426658
3166/3780 0.400 1.429 scale MinMaxScaler() 0 -> 0.47465091318931446
3167/3780 0.400 1.429 auto StandardScaler() 0 -> 0.472717017442666
3168/3780 0.400 1.429 auto MinMaxScaler() 0 -> 0.5335971816772237
3169/3780 0.400 1.429 0.01 StandardScaler() 0 -> 0.5015595522667914
3170/3780 0.400 1.429 0.01 MinMaxScaler() 0 -> 0.5679119620440285
3171/3780 0.400 1.429 0.03162277660168379 StandardScaler() 0 -> 0.48628534781754634
3172/3780 0.400 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5525473322326201
3173/3780 0.400 1.429 0.1 StandardScaler() 0 -> 0.47134048510466026
3174/3780 0.400 1.429 0.1 MinMaxScaler() 0 -> 0.5312805613186778
3175/3780 0.400 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4699784506517804
3176/3780 0.400 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5021707428781097
3177/3780 0.400 1.429 1.0 StandardScaler() 0 -> 0.5167481299758928
3178/3780 0.400 1.429 1.0 MinMaxScaler() 0 -> 0.48499337783802016
3179/3780 0.400 1.814 scale StandardScaler() 0 -> 0.47114229500157023
3180/3780 0.400 1.814 scale MinMaxScaler() 0 -> 0.47344113805972704
3181/3780 0.400 1.814 auto StandardScaler() 0 -> 0.4711422950015707
3182/3780 0.400 1.814 auto MinMaxScaler() 0 -> 0.5304991643644775
3183/3780 0.400 1.814 0.01 StandardScaler() 0 -> 0.49929815544719375
3184/3780 0.400 1.814 0.01 MinMaxScaler() 0 -> 0.5645232965017151
3185/3780 0.400 1.814 0.03162277660168379 StandardScaler() 0 -> 0.48519767031643973
3186/3780 0.400 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5504968906707647
3187/3780 0.400 1.814 0.1 StandardScaler() 0 -> 0.47057611983256864
3188/3780 0.400 1.814 0.1 MinMaxScaler() 0 -> 0.527782256840791
3189/3780 0.400 1.814 0.31622776601683794 StandardScaler() 0 -> 0.4708177278902239
3190/3780 0.400 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.4999036757182253
3191/3780 0.400 1.814 1.0 StandardScaler() 0 -> 0.5154294420703834
3192/3780 0.400 1.814 1.0 MinMaxScaler() 0 -> 0.48306303306623427
3193/3780 0.400 2.302 scale StandardScaler() 0 -> 0.47067669080014657
3194/3780 0.400 2.302 scale MinMaxScaler() 0 -> 0.4730641052547237
3195/3780 0.400 2.302 auto StandardScaler() 0 -> 0.4706766908001469
3196/3780 0.400 2.302 auto MinMaxScaler() 0 -> 0.5270209943383825
3197/3780 0.400 2.302 0.01 StandardScaler() 0 -> 0.49760536365312574
3198/3780 0.400 2.302 0.01 MinMaxScaler() 0 -> 0.5617626048744455
3199/3780 0.400 2.302 0.03162277660168379 StandardScaler() 0 -> 0.48409890353664337
3200/3780 0.400 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5485655550673436
3201/3780 0.400 2.302 0.1 StandardScaler() 0 -> 0.4713030154051163
3202/3780 0.400 2.302 0.1 MinMaxScaler() 0 -> 0.5240658688521589
3203/3780 0.400 2.302 0.31622776601683794 StandardScaler() 0 -> 0.4730724253201926
3204/3780 0.400 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.4976167484673047
3205/3780 0.400 2.302 1.0 StandardScaler() 0 -> 0.5151621695866774
3206/3780 0.400 2.302 1.0 MinMaxScaler() 0 -> 0.4816072017901763
3207/3780 0.400 2.921 scale StandardScaler() 0 -> 0.4718523757934272
3208/3780 0.400 2.921 scale MinMaxScaler() 0 -> 0.47330124249210037
3209/3780 0.400 2.921 auto StandardScaler() 0 -> 0.4718523757934268
3210/3780 0.400 2.921 auto MinMaxScaler() 0 -> 0.5233190804084765
3211/3780 0.400 2.921 0.01 StandardScaler() 0 -> 0.4959693574760841
3212/3780 0.400 2.921 0.01 MinMaxScaler() 0 -> 0.5590073626756619
3213/3780 0.400 2.921 0.03162277660168379 StandardScaler() 0 -> 0.48277571107254674
3214/3780 0.400 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.546572436061472
3215/3780 0.400 2.921 0.1 StandardScaler() 0 -> 0.47299551430776016
3216/3780 0.400 2.921 0.1 MinMaxScaler() 0 -> 0.5203253552880543
3217/3780 0.400 2.921 0.31622776601683794 StandardScaler() 0 -> 0.477467068708976
3218/3780 0.400 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.49593086302178463
3219/3780 0.400 2.921 1.0 StandardScaler() 0 -> 0.5151065676055252
3220/3780 0.400 2.921 1.0 MinMaxScaler() 0 -> 0.480445576411405
3221/3780 0.400 3.707 scale StandardScaler() 0 -> 0.4738984813233416
3222/3780 0.400 3.707 scale MinMaxScaler() 0 -> 0.47364939036508225
3223/3780 0.400 3.707 auto StandardScaler() 0 -> 0.47389848132334217
3224/3780 0.400 3.707 auto MinMaxScaler() 0 -> 0.5194400476154013
3225/3780 0.400 3.707 0.01 StandardScaler() 0 -> 0.49485444179874527
3226/3780 0.400 3.707 0.01 MinMaxScaler() 0 -> 0.5572919795733057
3227/3780 0.400 3.707 0.03162277660168379 StandardScaler() 0 -> 0.4812563289464398
3228/3780 0.400 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5444481355958161
3229/3780 0.400 3.707 0.1 StandardScaler() 0 -> 0.4746977752082347
3230/3780 0.400 3.707 0.1 MinMaxScaler() 0 -> 0.5168859710027296
3231/3780 0.400 3.707 0.31622776601683794 StandardScaler() 0 -> 0.4814879923096138
3232/3780 0.400 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.4940189531058226
3233/3780 0.400 3.707 1.0 StandardScaler() 0 -> 0.515103518306116
3234/3780 0.400 3.707 1.0 MinMaxScaler() 0 -> 0.47933322263714323
3235/3780 0.400 4.703 scale StandardScaler() 0 -> 0.4761154189608927
3236/3780 0.400 4.703 scale MinMaxScaler() 0 -> 0.4750310333734074
3237/3780 0.400 4.703 auto StandardScaler() 0 -> 0.4761154189608931
3238/3780 0.400 4.703 auto MinMaxScaler() 0 -> 0.5163059635443469
3239/3780 0.400 4.703 0.01 StandardScaler() 0 -> 0.49391744100038487
3240/3780 0.400 4.703 0.01 MinMaxScaler() 0 -> 0.5547219075934394
3241/3780 0.400 4.703 0.03162277660168379 StandardScaler() 0 -> 0.4807566222370924
3242/3780 0.400 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.542473496664772
3243/3780 0.400 4.703 0.1 StandardScaler() 0 -> 0.47620759852881184
3244/3780 0.400 4.703 0.1 MinMaxScaler() 0 -> 0.5142186010987535
3245/3780 0.400 4.703 0.31622776601683794 StandardScaler() 0 -> 0.4853568083650794
3246/3780 0.400 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.49299596451072597
3247/3780 0.400 4.703 1.0 StandardScaler() 0 -> 0.5151068521918094
3248/3780 0.400 4.703 1.0 MinMaxScaler() 0 -> 0.4784549560535409
3249/3780 0.400 5.968 scale StandardScaler() 0 -> 0.4782243877523376
3250/3780 0.400 5.968 scale MinMaxScaler() 0 -> 0.4777302747584533
3251/3780 0.400 5.968 auto StandardScaler() 0 -> 0.47822438775233783
3252/3780 0.400 5.968 auto MinMaxScaler() 0 -> 0.5134866158230502
3253/3780 0.400 5.968 0.01 StandardScaler() 0 -> 0.4930595159424322
3254/3780 0.400 5.968 0.01 MinMaxScaler() 0 -> 0.5536150638768133
3255/3780 0.400 5.968 0.03162277660168379 StandardScaler() 0 -> 0.48015509747598034
3256/3780 0.400 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5399559459451543
3257/3780 0.400 5.968 0.1 StandardScaler() 0 -> 0.479303107185786
3258/3780 0.400 5.968 0.1 MinMaxScaler() 0 -> 0.511090144649015
3259/3780 0.400 5.968 0.31622776601683794 StandardScaler() 0 -> 0.48917152374828027
3260/3780 0.400 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.49247159323970413
3261/3780 0.400 5.968 1.0 StandardScaler() 0 -> 0.5151068521918094
3262/3780 0.400 5.968 1.0 MinMaxScaler() 0 -> 0.4775319182999092
3263/3780 0.400 7.574 scale StandardScaler() 0 -> 0.4816257920448706
3264/3780 0.400 7.574 scale MinMaxScaler() 0 -> 0.48034063096029983
3265/3780 0.400 7.574 auto StandardScaler() 0 -> 0.4816257920448687
3266/3780 0.400 7.574 auto MinMaxScaler() 0 -> 0.5104478906806118
3267/3780 0.400 7.574 0.01 StandardScaler() 0 -> 0.4926150296849913
3268/3780 0.400 7.574 0.01 MinMaxScaler() 0 -> 0.5524464610406308
3269/3780 0.400 7.574 0.03162277660168379 StandardScaler() 0 -> 0.4786628413851955
3270/3780 0.400 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5376422089990255
3271/3780 0.400 7.574 0.1 StandardScaler() 0 -> 0.4847402336433295
3272/3780 0.400 7.574 0.1 MinMaxScaler() 0 -> 0.5080261665219655
3273/3780 0.400 7.574 0.31622776601683794 StandardScaler() 0 -> 0.4927368473858988
3274/3780 0.400 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.49203693927946074
3275/3780 0.400 7.574 1.0 StandardScaler() 0 -> 0.5151068521918094
3276/3780 0.400 7.574 1.0 MinMaxScaler() 0 -> 0.4770418475118407
3277/3780 0.400 9.611 scale StandardScaler() 0 -> 0.48747189980500333
3278/3780 0.400 9.611 scale MinMaxScaler() 0 -> 0.48319162494994905
3279/3780 0.400 9.611 auto StandardScaler() 0 -> 0.4874718998050029
3280/3780 0.400 9.611 auto MinMaxScaler() 0 -> 0.5073666103058
3281/3780 0.400 9.611 0.01 StandardScaler() 0 -> 0.49203371879771834
3282/3780 0.400 9.611 0.01 MinMaxScaler() 0 -> 0.5514071386381211
3283/3780 0.400 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4774115241741765
3284/3780 0.400 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.534578438183844
3285/3780 0.400 9.611 0.1 StandardScaler() 0 -> 0.49197525844160234
3286/3780 0.400 9.611 0.1 MinMaxScaler() 0 -> 0.505739088558152
3287/3780 0.400 9.611 0.31622776601683794 StandardScaler() 0 -> 0.4957515031470971
3288/3780 0.400 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4914232435349734
3289/3780 0.400 9.611 1.0 StandardScaler() 0 -> 0.5151068521918094
3290/3780 0.400 9.611 1.0 MinMaxScaler() 0 -> 0.4766432285345111
3291/3780 0.400 12.196 scale StandardScaler() 0 -> 0.4953015368858514
3292/3780 0.400 12.196 scale MinMaxScaler() 0 -> 0.486757086754464
3293/3780 0.400 12.196 auto StandardScaler() 0 -> 0.49530153688585005
3294/3780 0.400 12.196 auto MinMaxScaler() 0 -> 0.505280099534264
3295/3780 0.400 12.196 0.01 StandardScaler() 0 -> 0.49100274196447424
3296/3780 0.400 12.196 0.01 MinMaxScaler() 0 -> 0.5503686653452013
3297/3780 0.400 12.196 0.03162277660168379 StandardScaler() 0 -> 0.47713641234035215
3298/3780 0.400 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5317212418775755
3299/3780 0.400 12.196 0.1 StandardScaler() 0 -> 0.4997107045590185
3300/3780 0.400 12.196 0.1 MinMaxScaler() 0 -> 0.5029011864148639
3301/3780 0.400 12.196 0.31622776601683794 StandardScaler() 0 -> 0.4980952191881396
3302/3780 0.400 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4903170404798756
3303/3780 0.400 12.196 1.0 StandardScaler() 0 -> 0.5151068521918094
3304/3780 0.400 12.196 1.0 MinMaxScaler() 0 -> 0.47665118086217845
3305/3780 0.400 15.476 scale StandardScaler() 0 -> 0.5035239857054766
3306/3780 0.400 15.476 scale MinMaxScaler() 0 -> 0.492139421263992
3307/3780 0.400 15.476 auto StandardScaler() 0 -> 0.5035239857054786
3308/3780 0.400 15.476 auto MinMaxScaler() 0 -> 0.502665815301469
3309/3780 0.400 15.476 0.01 StandardScaler() 0 -> 0.4901081206743601
3310/3780 0.400 15.476 0.01 MinMaxScaler() 0 -> 0.5490832069056902
3311/3780 0.400 15.476 0.03162277660168379 StandardScaler() 0 -> 0.4778203626125767
3312/3780 0.400 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5286021570359379
3313/3780 0.400 15.476 0.1 StandardScaler() 0 -> 0.5096684997173074
3314/3780 0.400 15.476 0.1 MinMaxScaler() 0 -> 0.5008317371101537
3315/3780 0.400 15.476 0.31622776601683794 StandardScaler() 0 -> 0.4997921835785659
3316/3780 0.400 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.48933054196397946
3317/3780 0.400 15.476 1.0 StandardScaler() 0 -> 0.5151068521918094
3318/3780 0.400 15.476 1.0 MinMaxScaler() 0 -> 0.4769864139703361
3319/3780 0.400 19.638 scale StandardScaler() 0 -> 0.5141398304167493
3320/3780 0.400 19.638 scale MinMaxScaler() 0 -> 0.49941186614632244
3321/3780 0.400 19.638 auto StandardScaler() 0 -> 0.5141398304167429
3322/3780 0.400 19.638 auto MinMaxScaler() 0 -> 0.5004840855818836
3323/3780 0.400 19.638 0.01 StandardScaler() 0 -> 0.4894327924717479
3324/3780 0.400 19.638 0.01 MinMaxScaler() 0 -> 0.548014852244683
3325/3780 0.400 19.638 0.03162277660168379 StandardScaler() 0 -> 0.47993071490681044
3326/3780 0.400 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.5251658136096595
3327/3780 0.400 19.638 0.1 StandardScaler() 0 -> 0.5203953018743205
3328/3780 0.400 19.638 0.1 MinMaxScaler() 0 -> 0.4989742577654197
3329/3780 0.400 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5006359962711633
3330/3780 0.400 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.48829797358513144
3331/3780 0.400 19.638 1.0 StandardScaler() 0 -> 0.5151068521918094
3332/3780 0.400 19.638 1.0 MinMaxScaler() 0 -> 0.4778385861408012
3333/3780 0.400 24.920 scale StandardScaler() 0 -> 0.5261855630142608
3334/3780 0.400 24.920 scale MinMaxScaler() 0 -> 0.5078150708770713
3335/3780 0.400 24.920 auto StandardScaler() 0 -> 0.526185563014258
3336/3780 0.400 24.920 auto MinMaxScaler() 0 -> 0.4985869761615431
3337/3780 0.400 24.920 0.01 StandardScaler() 0 -> 0.4884444245665301
3338/3780 0.400 24.920 0.01 MinMaxScaler() 0 -> 0.5463666605885923
3339/3780 0.400 24.920 0.03162277660168379 StandardScaler() 0 -> 0.4814162862311819
3340/3780 0.400 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.5214304049686534
3341/3780 0.400 24.920 0.1 StandardScaler() 0 -> 0.5331926290487382
3342/3780 0.400 24.920 0.1 MinMaxScaler() 0 -> 0.4975675657763821
3343/3780 0.400 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5007979010379894
3344/3780 0.400 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.48683884016810325
3345/3780 0.400 24.920 1.0 StandardScaler() 0 -> 0.5151068521918094
3346/3780 0.400 24.920 1.0 MinMaxScaler() 0 -> 0.48039781720317887
3347/3780 0.400 31.623 scale StandardScaler() 0 -> 0.5397856882696815
3348/3780 0.400 31.623 scale MinMaxScaler() 0 -> 0.5170873242012813
3349/3780 0.400 31.623 auto StandardScaler() 0 -> 0.5397856882696815
3350/3780 0.400 31.623 auto MinMaxScaler() 0 -> 0.49751022821955804
3351/3780 0.400 31.623 0.01 StandardScaler() 0 -> 0.4874769721945309
3352/3780 0.400 31.623 0.01 MinMaxScaler() 0 -> 0.5449252561656763
3353/3780 0.400 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4826508605766669
3354/3780 0.400 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.5180616707141478
3355/3780 0.400 31.623 0.1 StandardScaler() 0 -> 0.5498254044839045
3356/3780 0.400 31.623 0.1 MinMaxScaler() 0 -> 0.4966962162448815
3357/3780 0.400 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5009070817431202
3358/3780 0.400 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.48561689389132345
3359/3780 0.400 31.623 1.0 StandardScaler() 0 -> 0.5151068521918094
3360/3780 0.400 31.623 1.0 MinMaxScaler() 0 -> 0.48317723286465325
3361/3780 0.450 0.032 scale StandardScaler() 0 -> 0.548329305544668
3362/3780 0.450 0.032 scale MinMaxScaler() 0 -> 0.5441761813001467
3363/3780 0.450 0.032 auto StandardScaler() 0 -> 0.548329305544668
3364/3780 0.450 0.032 auto MinMaxScaler() 0 -> 0.6608142610575046
3365/3780 0.450 0.032 0.01 StandardScaler() 0 -> 0.5833469667070273
3366/3780 0.450 0.032 0.01 MinMaxScaler() 0 -> 0.8531470041813182
3367/3780 0.450 0.032 0.03162277660168379 StandardScaler() 0 -> 0.5538068394748552
3368/3780 0.450 0.032 0.03162277660168379 MinMaxScaler() 0 -> 0.787812139731233
3369/3780 0.450 0.032 0.1 StandardScaler() 0 -> 0.5498688643977955
3370/3780 0.450 0.032 0.1 MinMaxScaler() 0 -> 0.6476538775985855
3371/3780 0.450 0.032 0.31622776601683794 StandardScaler() 0 -> 0.6340989202051883
3372/3780 0.450 0.032 0.31622776601683794 MinMaxScaler() 0 -> 0.5757372196488215
3373/3780 0.450 0.032 1.0 StandardScaler() 0 -> 0.8576703363665431
3374/3780 0.450 0.032 1.0 MinMaxScaler() 0 -> 0.5499360385711161
3375/3780 0.450 0.040 scale StandardScaler() 0 -> 0.5398092718810226
3376/3780 0.450 0.040 scale MinMaxScaler() 0 -> 0.5375526572571406
3377/3780 0.450 0.040 auto StandardScaler() 0 -> 0.5398092718810226
3378/3780 0.450 0.040 auto MinMaxScaler() 0 -> 0.6279942512500145
3379/3780 0.450 0.040 0.01 StandardScaler() 0 -> 0.5758274321945419
3380/3780 0.450 0.040 0.01 MinMaxScaler() 0 -> 0.8441990007274072
3381/3780 0.450 0.040 0.03162277660168379 StandardScaler() 0 -> 0.5472833602387016
3382/3780 0.450 0.040 0.03162277660168379 MinMaxScaler() 0 -> 0.7648817502442892
3383/3780 0.450 0.040 0.1 StandardScaler() 0 -> 0.5410184165150601
3384/3780 0.450 0.040 0.1 MinMaxScaler() 0 -> 0.617635274685311
3385/3780 0.450 0.040 0.31622776601683794 StandardScaler() 0 -> 0.6146173865367905
3386/3780 0.450 0.040 0.31622776601683794 MinMaxScaler() 0 -> 0.5692419281138137
3387/3780 0.450 0.040 1.0 StandardScaler() 0 -> 0.849640327270361
3388/3780 0.450 0.040 1.0 MinMaxScaler() 0 -> 0.5432400331724413
3389/3780 0.450 0.051 scale StandardScaler() 0 -> 0.5329687078325699
3390/3780 0.450 0.051 scale MinMaxScaler() 0 -> 0.5313441211180433
3391/3780 0.450 0.051 auto StandardScaler() 0 -> 0.5329687078325699
3392/3780 0.450 0.051 auto MinMaxScaler() 0 -> 0.6045601008283735
3393/3780 0.450 0.051 0.01 StandardScaler() 0 -> 0.5688344369109554
3394/3780 0.450 0.051 0.01 MinMaxScaler() 0 -> 0.8330745072573075
3395/3780 0.450 0.051 0.03162277660168379 StandardScaler() 0 -> 0.5406726947894772
3396/3780 0.450 0.051 0.03162277660168379 MinMaxScaler() 0 -> 0.7376978221637858
3397/3780 0.450 0.051 0.1 StandardScaler() 0 -> 0.5339141803639528
3398/3780 0.450 0.051 0.1 MinMaxScaler() 0 -> 0.5988178956918199
3399/3780 0.450 0.051 0.31622776601683794 StandardScaler() 0 -> 0.5965860752820512
3400/3780 0.450 0.051 0.31622776601683794 MinMaxScaler() 0 -> 0.56354355294863
3401/3780 0.450 0.051 1.0 StandardScaler() 0 -> 0.8388722593103832
3402/3780 0.450 0.051 1.0 MinMaxScaler() 0 -> 0.5377894077088874
3403/3780 0.450 0.065 scale StandardScaler() 0 -> 0.5264135312431435
3404/3780 0.450 0.065 scale MinMaxScaler() 0 -> 0.5258433236248675
3405/3780 0.450 0.065 auto StandardScaler() 0 -> 0.5264135312431435
3406/3780 0.450 0.065 auto MinMaxScaler() 0 -> 0.5919609610293778
3407/3780 0.450 0.065 0.01 StandardScaler() 0 -> 0.5631805895179575
3408/3780 0.450 0.065 0.01 MinMaxScaler() 0 -> 0.8193624789290509
3409/3780 0.450 0.065 0.03162277660168379 StandardScaler() 0 -> 0.5343863814421671
3410/3780 0.450 0.065 0.03162277660168379 MinMaxScaler() 0 -> 0.7056749779623521
3411/3780 0.450 0.065 0.1 StandardScaler() 0 -> 0.5269058964861433
3412/3780 0.450 0.065 0.1 MinMaxScaler() 0 -> 0.5880252826344311
3413/3780 0.450 0.065 0.31622776601683794 StandardScaler() 0 -> 0.5795590634363732
3414/3780 0.450 0.065 0.31622776601683794 MinMaxScaler() 0 -> 0.55787566088346
3415/3780 0.450 0.065 1.0 StandardScaler() 0 -> 0.8239669312842199
3416/3780 0.450 0.065 1.0 MinMaxScaler() 0 -> 0.5320826533174238
3417/3780 0.450 0.082 scale StandardScaler() 0 -> 0.5197884838609933
3418/3780 0.450 0.082 scale MinMaxScaler() 0 -> 0.5202082452372366
3419/3780 0.450 0.082 auto StandardScaler() 0 -> 0.5197884838609933
3420/3780 0.450 0.082 auto MinMaxScaler() 0 -> 0.583719587164917
3421/3780 0.450 0.082 0.01 StandardScaler() 0 -> 0.5574473789703127
3422/3780 0.450 0.082 0.01 MinMaxScaler() 0 -> 0.8026721628508512
3423/3780 0.450 0.082 0.03162277660168379 StandardScaler() 0 -> 0.5279530146683359
3424/3780 0.450 0.082 0.03162277660168379 MinMaxScaler() 0 -> 0.6703232497178601
3425/3780 0.450 0.082 0.1 StandardScaler() 0 -> 0.5199653253740318
3426/3780 0.450 0.082 0.1 MinMaxScaler() 0 -> 0.5806785231098631
3427/3780 0.450 0.082 0.31622776601683794 StandardScaler() 0 -> 0.5642666755390963
3428/3780 0.450 0.082 0.31622776601683794 MinMaxScaler() 0 -> 0.5527634674258924
3429/3780 0.450 0.082 1.0 StandardScaler() 0 -> 0.8031700338752698
3430/3780 0.450 0.082 1.0 MinMaxScaler() 0 -> 0.5277055438440268
3431/3780 0.450 0.104 scale StandardScaler() 0 -> 0.5131164339707927
3432/3780 0.450 0.104 scale MinMaxScaler() 0 -> 0.5148889196876282
3433/3780 0.450 0.104 auto StandardScaler() 0 -> 0.5131164339707927
3434/3780 0.450 0.104 auto MinMaxScaler() 0 -> 0.5769514723685526
3435/3780 0.450 0.104 0.01 StandardScaler() 0 -> 0.5524490787058486
3436/3780 0.450 0.104 0.01 MinMaxScaler() 0 -> 0.783137261381722
3437/3780 0.450 0.104 0.03162277660168379 StandardScaler() 0 -> 0.5232612257434305
3438/3780 0.450 0.104 0.03162277660168379 MinMaxScaler() 0 -> 0.6364814480343091
3439/3780 0.450 0.104 0.1 StandardScaler() 0 -> 0.5132483482638236
3440/3780 0.450 0.104 0.1 MinMaxScaler() 0 -> 0.5746977986409688
3441/3780 0.450 0.104 0.31622776601683794 StandardScaler() 0 -> 0.5502920675419452
3442/3780 0.450 0.104 0.31622776601683794 MinMaxScaler() 0 -> 0.5475403503544571
3443/3780 0.450 0.104 1.0 StandardScaler() 0 -> 0.7745648327931062
3444/3780 0.450 0.104 1.0 MinMaxScaler() 0 -> 0.5225841547334992
3445/3780 0.450 0.132 scale StandardScaler() 0 -> 0.5070682101188038
3446/3780 0.450 0.132 scale MinMaxScaler() 0 -> 0.5105138653517433
3447/3780 0.450 0.132 auto StandardScaler() 0 -> 0.5070682101188038
3448/3780 0.450 0.132 auto MinMaxScaler() 0 -> 0.5712521501593449
3449/3780 0.450 0.132 0.01 StandardScaler() 0 -> 0.5466859040457744
3450/3780 0.450 0.132 0.01 MinMaxScaler() 0 -> 0.7589119137924603
3451/3780 0.450 0.132 0.03162277660168379 StandardScaler() 0 -> 0.5187489662221116
3452/3780 0.450 0.132 0.03162277660168379 MinMaxScaler() 0 -> 0.6106711745146388
3453/3780 0.450 0.132 0.1 StandardScaler() 0 -> 0.5069145277697659
3454/3780 0.450 0.132 0.1 MinMaxScaler() 0 -> 0.5692625648410284
3455/3780 0.450 0.132 0.31622776601683794 StandardScaler() 0 -> 0.5387185100249176
3456/3780 0.450 0.132 0.31622776601683794 MinMaxScaler() 0 -> 0.5421176352063579
3457/3780 0.450 0.132 1.0 StandardScaler() 0 -> 0.738297997691975
3458/3780 0.450 0.132 1.0 MinMaxScaler() 0 -> 0.5187613482036829
3459/3780 0.450 0.168 scale StandardScaler() 0 -> 0.5023922769043548
3460/3780 0.450 0.168 scale MinMaxScaler() 0 -> 0.5060952602673088
3461/3780 0.450 0.168 auto StandardScaler() 0 -> 0.5023922769043547
3462/3780 0.450 0.168 auto MinMaxScaler() 0 -> 0.5666283374617075
3463/3780 0.450 0.168 0.01 StandardScaler() 0 -> 0.5410051593324656
3464/3780 0.450 0.168 0.01 MinMaxScaler() 0 -> 0.7313698512822485
3465/3780 0.450 0.168 0.03162277660168379 StandardScaler() 0 -> 0.5147500188755025
3466/3780 0.450 0.168 0.03162277660168379 MinMaxScaler() 0 -> 0.5960930286960427
3467/3780 0.450 0.168 0.1 StandardScaler() 0 -> 0.502405500777195
3468/3780 0.450 0.168 0.1 MinMaxScaler() 0 -> 0.5646519521427399
3469/3780 0.450 0.168 0.31622776601683794 StandardScaler() 0 -> 0.5278479497302363
3470/3780 0.450 0.168 0.31622776601683794 MinMaxScaler() 0 -> 0.5380979759812704
3471/3780 0.450 0.168 1.0 StandardScaler() 0 -> 0.6964813578513406
3472/3780 0.450 0.168 1.0 MinMaxScaler() 0 -> 0.5149137209118145
3473/3780 0.450 0.213 scale StandardScaler() 0 -> 0.4984654204984908
3474/3780 0.450 0.213 scale MinMaxScaler() 0 -> 0.5011330942845506
3475/3780 0.450 0.213 auto StandardScaler() 0 -> 0.4984654204984907
3476/3780 0.450 0.213 auto MinMaxScaler() 0 -> 0.5620683146583151
3477/3780 0.450 0.213 0.01 StandardScaler() 0 -> 0.5359508468346318
3478/3780 0.450 0.213 0.01 MinMaxScaler() 0 -> 0.6974258496238607
3479/3780 0.450 0.213 0.03162277660168379 StandardScaler() 0 -> 0.510417833896471
3480/3780 0.450 0.213 0.03162277660168379 MinMaxScaler() 0 -> 0.5864750962421338
3481/3780 0.450 0.213 0.1 StandardScaler() 0 -> 0.4986182611393351
3482/3780 0.450 0.213 0.1 MinMaxScaler() 0 -> 0.5602932820151909
3483/3780 0.450 0.213 0.31622776601683794 StandardScaler() 0 -> 0.5186297973426893
3484/3780 0.450 0.213 0.31622776601683794 MinMaxScaler() 0 -> 0.5338610406289681
3485/3780 0.450 0.213 1.0 StandardScaler() 0 -> 0.6547963093819892
3486/3780 0.450 0.213 1.0 MinMaxScaler() 0 -> 0.5101148471239428
3487/3780 0.450 0.270 scale StandardScaler() 0 -> 0.4954001247393011
3488/3780 0.450 0.270 scale MinMaxScaler() 0 -> 0.49729722970554224
3489/3780 0.450 0.270 auto StandardScaler() 0 -> 0.495400124739301
3490/3780 0.450 0.270 auto MinMaxScaler() 0 -> 0.5582427098153947
3491/3780 0.450 0.270 0.01 StandardScaler() 0 -> 0.5316199399576913
3492/3780 0.450 0.270 0.01 MinMaxScaler() 0 -> 0.6623886455895489
3493/3780 0.450 0.270 0.03162277660168379 StandardScaler() 0 -> 0.5061558327074694
3494/3780 0.450 0.270 0.03162277660168379 MinMaxScaler() 0 -> 0.5798994748920396
3495/3780 0.450 0.270 0.1 StandardScaler() 0 -> 0.4957087982019835
3496/3780 0.450 0.270 0.1 MinMaxScaler() 0 -> 0.5563291779061618
3497/3780 0.450 0.270 0.31622776601683794 StandardScaler() 0 -> 0.5095591077117908
3498/3780 0.450 0.270 0.31622776601683794 MinMaxScaler() 0 -> 0.5297921909197886
3499/3780 0.450 0.270 1.0 StandardScaler() 0 -> 0.6184905149992
3500/3780 0.450 0.270 1.0 MinMaxScaler() 0 -> 0.5070817839649965
3501/3780 0.450 0.342 scale StandardScaler() 0 -> 0.49235457177274844
3502/3780 0.450 0.342 scale MinMaxScaler() 0 -> 0.4942663282552579
3503/3780 0.450 0.342 auto StandardScaler() 0 -> 0.49235457177274844
3504/3780 0.450 0.342 auto MinMaxScaler() 0 -> 0.5544768679083251
3505/3780 0.450 0.342 0.01 StandardScaler() 0 -> 0.5275895942986853
3506/3780 0.450 0.342 0.01 MinMaxScaler() 0 -> 0.6297901728947867
3507/3780 0.450 0.342 0.03162277660168379 StandardScaler() 0 -> 0.5025762942957317
3508/3780 0.450 0.342 0.03162277660168379 MinMaxScaler() 0 -> 0.5746572399306884
3509/3780 0.450 0.342 0.1 StandardScaler() 0 -> 0.49214893456141295
3510/3780 0.450 0.342 0.1 MinMaxScaler() 0 -> 0.552314367298062
3511/3780 0.450 0.342 0.31622776601683794 StandardScaler() 0 -> 0.5012043413821323
3512/3780 0.450 0.342 0.31622776601683794 MinMaxScaler() 0 -> 0.5261721051811181
3513/3780 0.450 0.342 1.0 StandardScaler() 0 -> 0.588377323000724
3514/3780 0.450 0.342 1.0 MinMaxScaler() 0 -> 0.5036566367933278
3515/3780 0.450 0.434 scale StandardScaler() 0 -> 0.48938831433947794
3516/3780 0.450 0.434 scale MinMaxScaler() 0 -> 0.49182199677413246
3517/3780 0.450 0.434 auto StandardScaler() 0 -> 0.489388314339478
3518/3780 0.450 0.434 auto MinMaxScaler() 0 -> 0.5507968085350808
3519/3780 0.450 0.434 0.01 StandardScaler() 0 -> 0.5237165065600841
3520/3780 0.450 0.434 0.01 MinMaxScaler() 0 -> 0.6064480145060581
3521/3780 0.450 0.434 0.03162277660168379 StandardScaler() 0 -> 0.4997598342415159
3522/3780 0.450 0.434 0.03162277660168379 MinMaxScaler() 0 -> 0.569807319501548
3523/3780 0.450 0.434 0.1 StandardScaler() 0 -> 0.4891840776632437
3524/3780 0.450 0.434 0.1 MinMaxScaler() 0 -> 0.5488338064411834
3525/3780 0.450 0.434 0.31622776601683794 StandardScaler() 0 -> 0.4943842813213431
3526/3780 0.450 0.434 0.31622776601683794 MinMaxScaler() 0 -> 0.5219702803265261
3527/3780 0.450 0.434 1.0 StandardScaler() 0 -> 0.5657233582584346
3528/3780 0.450 0.434 1.0 MinMaxScaler() 0 -> 0.500590631984735
3529/3780 0.450 0.551 scale StandardScaler() 0 -> 0.48677763847071165
3530/3780 0.450 0.551 scale MinMaxScaler() 0 -> 0.4889219018845577
3531/3780 0.450 0.551 auto StandardScaler() 0 -> 0.4867776384707116
3532/3780 0.450 0.551 auto MinMaxScaler() 0 -> 0.5475029495997489
3533/3780 0.450 0.551 0.01 StandardScaler() 0 -> 0.5198053582427539
3534/3780 0.450 0.551 0.01 MinMaxScaler() 0 -> 0.5937545591822401
3535/3780 0.450 0.551 0.03162277660168379 StandardScaler() 0 -> 0.4967171913616813
3536/3780 0.450 0.551 0.03162277660168379 MinMaxScaler() 0 -> 0.5657560559183609
3537/3780 0.450 0.551 0.1 StandardScaler() 0 -> 0.48600666042463897
3538/3780 0.450 0.551 0.1 MinMaxScaler() 0 -> 0.5457653857928663
3539/3780 0.450 0.551 0.31622776601683794 StandardScaler() 0 -> 0.48812586529926416
3540/3780 0.450 0.551 0.31622776601683794 MinMaxScaler() 0 -> 0.51807955993581
3541/3780 0.450 0.551 1.0 StandardScaler() 0 -> 0.5496182637926837
3542/3780 0.450 0.551 1.0 MinMaxScaler() 0 -> 0.4973882098701765
3543/3780 0.450 0.700 scale StandardScaler() 0 -> 0.4836645062745886
3544/3780 0.450 0.700 scale MinMaxScaler() 0 -> 0.48644100445267857
3545/3780 0.450 0.700 auto StandardScaler() 0 -> 0.48366450627458857
3546/3780 0.450 0.700 auto MinMaxScaler() 0 -> 0.5445999119968875
3547/3780 0.450 0.700 0.01 StandardScaler() 0 -> 0.51512025264153
3548/3780 0.450 0.700 0.01 MinMaxScaler() 0 -> 0.5852953258421691
3549/3780 0.450 0.700 0.03162277660168379 StandardScaler() 0 -> 0.49423063114326077
3550/3780 0.450 0.700 0.03162277660168379 MinMaxScaler() 0 -> 0.5622921576385879
3551/3780 0.450 0.700 0.1 StandardScaler() 0 -> 0.4825290420100758
3552/3780 0.450 0.700 0.1 MinMaxScaler() 0 -> 0.542601694969468
3553/3780 0.450 0.700 0.31622776601683794 StandardScaler() 0 -> 0.4830543602243327
3554/3780 0.450 0.700 0.31622776601683794 MinMaxScaler() 0 -> 0.5144427927010632
3555/3780 0.450 0.700 1.0 StandardScaler() 0 -> 0.5405128811351695
3556/3780 0.450 0.700 1.0 MinMaxScaler() 0 -> 0.4943550279636759
3557/3780 0.450 0.888 scale StandardScaler() 0 -> 0.4811168378108977
3558/3780 0.450 0.888 scale MinMaxScaler() 0 -> 0.48353840811072324
3559/3780 0.450 0.888 auto StandardScaler() 0 -> 0.4811168378108976
3560/3780 0.450 0.888 auto MinMaxScaler() 0 -> 0.5416048560436558
3561/3780 0.450 0.888 0.01 StandardScaler() 0 -> 0.5116871213236055
3562/3780 0.450 0.888 0.01 MinMaxScaler() 0 -> 0.5788423644053456
3563/3780 0.450 0.888 0.03162277660168379 StandardScaler() 0 -> 0.4921078739072911
3564/3780 0.450 0.888 0.03162277660168379 MinMaxScaler() 0 -> 0.5594025422027321
3565/3780 0.450 0.888 0.1 StandardScaler() 0 -> 0.4798651313968756
3566/3780 0.450 0.888 0.1 MinMaxScaler() 0 -> 0.5395714838620568
3567/3780 0.450 0.888 0.31622776601683794 StandardScaler() 0 -> 0.47921380767238514
3568/3780 0.450 0.888 0.31622776601683794 MinMaxScaler() 0 -> 0.5113005756350928
3569/3780 0.450 0.888 1.0 StandardScaler() 0 -> 0.534293241823662
3570/3780 0.450 0.888 1.0 MinMaxScaler() 0 -> 0.49173141425621764
3571/3780 0.450 1.126 scale StandardScaler() 0 -> 0.47881740475166046
3572/3780 0.450 1.126 scale MinMaxScaler() 0 -> 0.48095593830641
3573/3780 0.450 1.126 auto StandardScaler() 0 -> 0.4788174047516606
3574/3780 0.450 1.126 auto MinMaxScaler() 0 -> 0.538777246331529
3575/3780 0.450 1.126 0.01 StandardScaler() 0 -> 0.508347023103202
3576/3780 0.450 1.126 0.01 MinMaxScaler() 0 -> 0.5741007110037734
3577/3780 0.450 1.126 0.03162277660168379 StandardScaler() 0 -> 0.48977264361357636
3578/3780 0.450 1.126 0.03162277660168379 MinMaxScaler() 0 -> 0.5567529238970904
3579/3780 0.450 1.126 0.1 StandardScaler() 0 -> 0.4774491552063668
3580/3780 0.450 1.126 0.1 MinMaxScaler() 0 -> 0.5364371501233297
3581/3780 0.450 1.126 0.31622776601683794 StandardScaler() 0 -> 0.4766216522691495
3582/3780 0.450 1.126 0.31622776601683794 MinMaxScaler() 0 -> 0.5085940608129274
3583/3780 0.450 1.126 1.0 StandardScaler() 0 -> 0.5285495572989034
3584/3780 0.450 1.126 1.0 MinMaxScaler() 0 -> 0.489678932396644
3585/3780 0.450 1.429 scale StandardScaler() 0 -> 0.47686351691198275
3586/3780 0.450 1.429 scale MinMaxScaler() 0 -> 0.47910766516359615
3587/3780 0.450 1.429 auto StandardScaler() 0 -> 0.47686351691198325
3588/3780 0.450 1.429 auto MinMaxScaler() 0 -> 0.5354004570689422
3589/3780 0.450 1.429 0.01 StandardScaler() 0 -> 0.5058377813507223
3590/3780 0.450 1.429 0.01 MinMaxScaler() 0 -> 0.5699713537205832
3591/3780 0.450 1.429 0.03162277660168379 StandardScaler() 0 -> 0.4884472527341371
3592/3780 0.450 1.429 0.03162277660168379 MinMaxScaler() 0 -> 0.5541553721021799
3593/3780 0.450 1.429 0.1 StandardScaler() 0 -> 0.4755583305641609
3594/3780 0.450 1.429 0.1 MinMaxScaler() 0 -> 0.5326438481085489
3595/3780 0.450 1.429 0.31622776601683794 StandardScaler() 0 -> 0.4758708328189518
3596/3780 0.450 1.429 0.31622776601683794 MinMaxScaler() 0 -> 0.5059396314077337
3597/3780 0.450 1.429 1.0 StandardScaler() 0 -> 0.5243544643226684
3598/3780 0.450 1.429 1.0 MinMaxScaler() 0 -> 0.48834402911282576
3599/3780 0.450 1.814 scale StandardScaler() 0 -> 0.4754635217066419
3600/3780 0.450 1.814 scale MinMaxScaler() 0 -> 0.47802238601797503
3601/3780 0.450 1.814 auto StandardScaler() 0 -> 0.475463521706642
3602/3780 0.450 1.814 auto MinMaxScaler() 0 -> 0.5315286541450747
3603/3780 0.450 1.814 0.01 StandardScaler() 0 -> 0.5030795699909756
3604/3780 0.450 1.814 0.01 MinMaxScaler() 0 -> 0.5656030898993977
3605/3780 0.450 1.814 0.03162277660168379 StandardScaler() 0 -> 0.48780764092691414
3606/3780 0.450 1.814 0.03162277660168379 MinMaxScaler() 0 -> 0.5519704178249606
3607/3780 0.450 1.814 0.1 StandardScaler() 0 -> 0.4747651270560531
3608/3780 0.450 1.814 0.1 MinMaxScaler() 0 -> 0.5290761378631353
3609/3780 0.450 1.814 0.31622776601683794 StandardScaler() 0 -> 0.47660453115566676
3610/3780 0.450 1.814 0.31622776601683794 MinMaxScaler() 0 -> 0.503689767297458
3611/3780 0.450 1.814 1.0 StandardScaler() 0 -> 0.5233349793033802
3612/3780 0.450 1.814 1.0 MinMaxScaler() 0 -> 0.4878061206527929
3613/3780 0.450 2.302 scale StandardScaler() 0 -> 0.4749901112961426
3614/3780 0.450 2.302 scale MinMaxScaler() 0 -> 0.477070864930063
3615/3780 0.450 2.302 auto StandardScaler() 0 -> 0.4749901112961424
3616/3780 0.450 2.302 auto MinMaxScaler() 0 -> 0.5281635982483964
3617/3780 0.450 2.302 0.01 StandardScaler() 0 -> 0.5004752946529579
3618/3780 0.450 2.302 0.01 MinMaxScaler() 0 -> 0.5630554097372046
3619/3780 0.450 2.302 0.03162277660168379 StandardScaler() 0 -> 0.4866795530926287
3620/3780 0.450 2.302 0.03162277660168379 MinMaxScaler() 0 -> 0.5497943232361223
3621/3780 0.450 2.302 0.1 StandardScaler() 0 -> 0.47494446676718455
3622/3780 0.450 2.302 0.1 MinMaxScaler() 0 -> 0.525972953501438
3623/3780 0.450 2.302 0.31622776601683794 StandardScaler() 0 -> 0.47840633381637093
3624/3780 0.450 2.302 0.31622776601683794 MinMaxScaler() 0 -> 0.501502929437826
3625/3780 0.450 2.302 1.0 StandardScaler() 0 -> 0.523085684413927
3626/3780 0.450 2.302 1.0 MinMaxScaler() 0 -> 0.4866920892637309
3627/3780 0.450 2.921 scale StandardScaler() 0 -> 0.4754912718497278
3628/3780 0.450 2.921 scale MinMaxScaler() 0 -> 0.4768390566075529
3629/3780 0.450 2.921 auto StandardScaler() 0 -> 0.47549127184972767
3630/3780 0.450 2.921 auto MinMaxScaler() 0 -> 0.5252916102719324
3631/3780 0.450 2.921 0.01 StandardScaler() 0 -> 0.49877506849453185
3632/3780 0.450 2.921 0.01 MinMaxScaler() 0 -> 0.5602289769405954
3633/3780 0.450 2.921 0.03162277660168379 StandardScaler() 0 -> 0.4849953861427175
3634/3780 0.450 2.921 0.03162277660168379 MinMaxScaler() 0 -> 0.5481557172429515
3635/3780 0.450 2.921 0.1 StandardScaler() 0 -> 0.4761239378167235
3636/3780 0.450 2.921 0.1 MinMaxScaler() 0 -> 0.5231185727064414
3637/3780 0.450 2.921 0.31622776601683794 StandardScaler() 0 -> 0.4823937857784313
3638/3780 0.450 2.921 0.31622776601683794 MinMaxScaler() 0 -> 0.4989338081267052
3639/3780 0.450 2.921 1.0 StandardScaler() 0 -> 0.5230664091874556
3640/3780 0.450 2.921 1.0 MinMaxScaler() 0 -> 0.4855672265030469
3641/3780 0.450 3.707 scale StandardScaler() 0 -> 0.4772278902614377
3642/3780 0.450 3.707 scale MinMaxScaler() 0 -> 0.4767284216612319
3643/3780 0.450 3.707 auto StandardScaler() 0 -> 0.4772278902614376
3644/3780 0.450 3.707 auto MinMaxScaler() 0 -> 0.522240831334729
3645/3780 0.450 3.707 0.01 StandardScaler() 0 -> 0.49712307034900216
3646/3780 0.450 3.707 0.01 MinMaxScaler() 0 -> 0.5583866188665437
3647/3780 0.450 3.707 0.03162277660168379 StandardScaler() 0 -> 0.4838249328611503
3648/3780 0.450 3.707 0.03162277660168379 MinMaxScaler() 0 -> 0.5463972993740644
3649/3780 0.450 3.707 0.1 StandardScaler() 0 -> 0.477735364318494
3650/3780 0.450 3.707 0.1 MinMaxScaler() 0 -> 0.5197111911131597
3651/3780 0.450 3.707 0.31622776601683794 StandardScaler() 0 -> 0.4858428965277037
3652/3780 0.450 3.707 0.31622776601683794 MinMaxScaler() 0 -> 0.49670500146784885
3653/3780 0.450 3.707 1.0 StandardScaler() 0 -> 0.5230672085652285
3654/3780 0.450 3.707 1.0 MinMaxScaler() 0 -> 0.4834964969867565
3655/3780 0.450 4.703 scale StandardScaler() 0 -> 0.47928282870511757
3656/3780 0.450 4.703 scale MinMaxScaler() 0 -> 0.47800374093473375
3657/3780 0.450 4.703 auto StandardScaler() 0 -> 0.47928282870511785
3658/3780 0.450 4.703 auto MinMaxScaler() 0 -> 0.5189821727806853
3659/3780 0.450 4.703 0.01 StandardScaler() 0 -> 0.49566829921756694
3660/3780 0.450 4.703 0.01 MinMaxScaler() 0 -> 0.5562954795268881
3661/3780 0.450 4.703 0.03162277660168379 StandardScaler() 0 -> 0.48255485326466524
3662/3780 0.450 4.703 0.03162277660168379 MinMaxScaler() 0 -> 0.5442281135492104
3663/3780 0.450 4.703 0.1 StandardScaler() 0 -> 0.4799050262970251
3664/3780 0.450 4.703 0.1 MinMaxScaler() 0 -> 0.5165557298770461
3665/3780 0.450 4.703 0.31622776601683794 StandardScaler() 0 -> 0.4893874938974667
3666/3780 0.450 4.703 0.31622776601683794 MinMaxScaler() 0 -> 0.4954014964848139
3667/3780 0.450 4.703 1.0 StandardScaler() 0 -> 0.5230672085652285
3668/3780 0.450 4.703 1.0 MinMaxScaler() 0 -> 0.4819775691022819
3669/3780 0.450 5.968 scale StandardScaler() 0 -> 0.4819286758433099
3670/3780 0.450 5.968 scale MinMaxScaler() 0 -> 0.48041631122935824
3671/3780 0.450 5.968 auto StandardScaler() 0 -> 0.48192867584331106
3672/3780 0.450 5.968 auto MinMaxScaler() 0 -> 0.516043557006964
3673/3780 0.450 5.968 0.01 StandardScaler() 0 -> 0.4947095094489355
3674/3780 0.450 5.968 0.01 MinMaxScaler() 0 -> 0.5552218802256977
3675/3780 0.450 5.968 0.03162277660168379 StandardScaler() 0 -> 0.4815068049020044
3676/3780 0.450 5.968 0.03162277660168379 MinMaxScaler() 0 -> 0.5414611209803764
3677/3780 0.450 5.968 0.1 StandardScaler() 0 -> 0.4838634428791044
3678/3780 0.450 5.968 0.1 MinMaxScaler() 0 -> 0.5137150684909848
3679/3780 0.450 5.968 0.31622776601683794 StandardScaler() 0 -> 0.49282297447630746
3680/3780 0.450 5.968 0.31622776601683794 MinMaxScaler() 0 -> 0.49474655944401086
3681/3780 0.450 5.968 1.0 StandardScaler() 0 -> 0.5230672085652285
3682/3780 0.450 5.968 1.0 MinMaxScaler() 0 -> 0.48178490678741515
3683/3780 0.450 7.574 scale StandardScaler() 0 -> 0.48622730321944374
3684/3780 0.450 7.574 scale MinMaxScaler() 0 -> 0.4832762129743844
3685/3780 0.450 7.574 auto StandardScaler() 0 -> 0.48622730321944324
3686/3780 0.450 7.574 auto MinMaxScaler() 0 -> 0.5130486020787126
3687/3780 0.450 7.574 0.01 StandardScaler() 0 -> 0.49422168058201893
3688/3780 0.450 7.574 0.01 MinMaxScaler() 0 -> 0.5542321059379841
3689/3780 0.450 7.574 0.03162277660168379 StandardScaler() 0 -> 0.4808972796228373
3690/3780 0.450 7.574 0.03162277660168379 MinMaxScaler() 0 -> 0.5385062603475402
3691/3780 0.450 7.574 0.1 StandardScaler() 0 -> 0.48931086632585763
3692/3780 0.450 7.574 0.1 MinMaxScaler() 0 -> 0.5109541404753029
3693/3780 0.450 7.574 0.31622776601683794 StandardScaler() 0 -> 0.49598755121601035
3694/3780 0.450 7.574 0.31622776601683794 MinMaxScaler() 0 -> 0.49375537388711893
3695/3780 0.450 7.574 1.0 StandardScaler() 0 -> 0.5230672085652285
3696/3780 0.450 7.574 1.0 MinMaxScaler() 0 -> 0.48165136735374475
3697/3780 0.450 9.611 scale StandardScaler() 0 -> 0.4919668443725418
3698/3780 0.450 9.611 scale MinMaxScaler() 0 -> 0.4859598690559693
3699/3780 0.450 9.611 auto StandardScaler() 0 -> 0.4919668443725427
3700/3780 0.450 9.611 auto MinMaxScaler() 0 -> 0.5103578860854224
3701/3780 0.450 9.611 0.01 StandardScaler() 0 -> 0.49324445726478544
3702/3780 0.450 9.611 0.01 MinMaxScaler() 0 -> 0.5529042147267652
3703/3780 0.450 9.611 0.03162277660168379 StandardScaler() 0 -> 0.4804365978343666
3704/3780 0.450 9.611 0.03162277660168379 MinMaxScaler() 0 -> 0.5356913530352142
3705/3780 0.450 9.611 0.1 StandardScaler() 0 -> 0.4943396587633375
3706/3780 0.450 9.611 0.1 MinMaxScaler() 0 -> 0.5080585335624469
3707/3780 0.450 9.611 0.31622776601683794 StandardScaler() 0 -> 0.4984768781670465
3708/3780 0.450 9.611 0.31622776601683794 MinMaxScaler() 0 -> 0.4926644223183408
3709/3780 0.450 9.611 1.0 StandardScaler() 0 -> 0.5230672085652285
3710/3780 0.450 9.611 1.0 MinMaxScaler() 0 -> 0.4810729887991023
3711/3780 0.450 12.196 scale StandardScaler() 0 -> 0.49762422356224084
3712/3780 0.450 12.196 scale MinMaxScaler() 0 -> 0.48965948547372773
3713/3780 0.450 12.196 auto StandardScaler() 0 -> 0.4976242235622399
3714/3780 0.450 12.196 auto MinMaxScaler() 0 -> 0.5076589264890908
3715/3780 0.450 12.196 0.01 StandardScaler() 0 -> 0.49240785758419564
3716/3780 0.450 12.196 0.01 MinMaxScaler() 0 -> 0.5518542337668982
3717/3780 0.450 12.196 0.03162277660168379 StandardScaler() 0 -> 0.48116686568195854
3718/3780 0.450 12.196 0.03162277660168379 MinMaxScaler() 0 -> 0.5324168267396852
3719/3780 0.450 12.196 0.1 StandardScaler() 0 -> 0.5009846687980516
3720/3780 0.450 12.196 0.1 MinMaxScaler() 0 -> 0.5059413402181124
3721/3780 0.450 12.196 0.31622776601683794 StandardScaler() 0 -> 0.5004765447703856
3722/3780 0.450 12.196 0.31622776601683794 MinMaxScaler() 0 -> 0.4919141657665061
3723/3780 0.450 12.196 1.0 StandardScaler() 0 -> 0.5230672085652285
3724/3780 0.450 12.196 1.0 MinMaxScaler() 0 -> 0.48038364901538183
3725/3780 0.450 15.476 scale StandardScaler() 0 -> 0.5047365592634129
3726/3780 0.450 15.476 scale MinMaxScaler() 0 -> 0.49506587337324554
3727/3780 0.450 15.476 auto StandardScaler() 0 -> 0.5047365592634164
3728/3780 0.450 15.476 auto MinMaxScaler() 0 -> 0.5053561152431744
3729/3780 0.450 15.476 0.01 StandardScaler() 0 -> 0.4918578169314339
3730/3780 0.450 15.476 0.01 MinMaxScaler() 0 -> 0.5505728563180313
3731/3780 0.450 15.476 0.03162277660168379 StandardScaler() 0 -> 0.48146276770874064
3732/3780 0.450 15.476 0.03162277660168379 MinMaxScaler() 0 -> 0.5291962464389601
3733/3780 0.450 15.476 0.1 StandardScaler() 0 -> 0.5093493948057078
3734/3780 0.450 15.476 0.1 MinMaxScaler() 0 -> 0.5034277362583172
3735/3780 0.450 15.476 0.31622776601683794 StandardScaler() 0 -> 0.5017976134804054
3736/3780 0.450 15.476 0.31622776601683794 MinMaxScaler() 0 -> 0.4912866793959098
3737/3780 0.450 15.476 1.0 StandardScaler() 0 -> 0.5230672085652285
3738/3780 0.450 15.476 1.0 MinMaxScaler() 0 -> 0.4801692991466444
3739/3780 0.450 19.638 scale StandardScaler() 0 -> 0.5141452040445386
3740/3780 0.450 19.638 scale MinMaxScaler() 0 -> 0.5024293464693843
3741/3780 0.450 19.638 auto StandardScaler() 0 -> 0.5141452040445376
3742/3780 0.450 19.638 auto MinMaxScaler() 0 -> 0.503079097024306
3743/3780 0.450 19.638 0.01 StandardScaler() 0 -> 0.49110172384394674
3744/3780 0.450 19.638 0.01 MinMaxScaler() 0 -> 0.5494348714522407
3745/3780 0.450 19.638 0.03162277660168379 StandardScaler() 0 -> 0.4821482289352581
3746/3780 0.450 19.638 0.03162277660168379 MinMaxScaler() 0 -> 0.526520149850148
3747/3780 0.450 19.638 0.1 StandardScaler() 0 -> 0.5196198599296006
3748/3780 0.450 19.638 0.1 MinMaxScaler() 0 -> 0.5019154139809947
3749/3780 0.450 19.638 0.31622776601683794 StandardScaler() 0 -> 0.5021695996974057
3750/3780 0.450 19.638 0.31622776601683794 MinMaxScaler() 0 -> 0.4900862856487918
3751/3780 0.450 19.638 1.0 StandardScaler() 0 -> 0.5230672085652285
3752/3780 0.450 19.638 1.0 MinMaxScaler() 0 -> 0.4806350858753663
3753/3780 0.450 24.920 scale StandardScaler() 0 -> 0.5249427149004148
3754/3780 0.450 24.920 scale MinMaxScaler() 0 -> 0.5102501609425348
3755/3780 0.450 24.920 auto StandardScaler() 0 -> 0.5249427149004184
3756/3780 0.450 24.920 auto MinMaxScaler() 0 -> 0.5015272495335558
3757/3780 0.450 24.920 0.01 StandardScaler() 0 -> 0.4900757537357469
3758/3780 0.450 24.920 0.01 MinMaxScaler() 0 -> 0.5481295515522341
3759/3780 0.450 24.920 0.03162277660168379 StandardScaler() 0 -> 0.483083649438017
3760/3780 0.450 24.920 0.03162277660168379 MinMaxScaler() 0 -> 0.524097329119726
3761/3780 0.450 24.920 0.1 StandardScaler() 0 -> 0.5331724716092653
3762/3780 0.450 24.920 0.1 MinMaxScaler() 0 -> 0.4998945610153169
3763/3780 0.450 24.920 0.31622776601683794 StandardScaler() 0 -> 0.5021776436214379
3764/3780 0.450 24.920 0.31622776601683794 MinMaxScaler() 0 -> 0.48933255769971734
3765/3780 0.450 24.920 1.0 StandardScaler() 0 -> 0.5230672085652285
3766/3780 0.450 24.920 1.0 MinMaxScaler() 0 -> 0.48215646321790934
3767/3780 0.450 31.623 scale StandardScaler() 0 -> 0.5395830427520681
3768/3780 0.450 31.623 scale MinMaxScaler() 0 -> 0.5185130421278207
3769/3780 0.450 31.623 auto StandardScaler() 0 -> 0.5395830427520715
3770/3780 0.450 31.623 auto MinMaxScaler() 0 -> 0.499747598747004
3771/3780 0.450 31.623 0.01 StandardScaler() 0 -> 0.4892514712875644
3772/3780 0.450 31.623 0.01 MinMaxScaler() 0 -> 0.5468627745301934
3773/3780 0.450 31.623 0.03162277660168379 StandardScaler() 0 -> 0.4849994699217743
3774/3780 0.450 31.623 0.03162277660168379 MinMaxScaler() 0 -> 0.520928594564566
3775/3780 0.450 31.623 0.1 StandardScaler() 0 -> 0.5491989079112227
3776/3780 0.450 31.623 0.1 MinMaxScaler() 0 -> 0.49886775305217396
3777/3780 0.450 31.623 0.31622776601683794 StandardScaler() 0 -> 0.5021776436214379
3778/3780 0.450 31.623 0.31622776601683794 MinMaxScaler() 0 -> 0.4883316009019687
3779/3780 0.450 31.623 1.0 StandardScaler() 0 -> 0.5230672085652285
3780/3780 0.450 31.623 1.0 MinMaxScaler() 0 -> 0.48348583377622817
Time Taken 10583.299s
Im folgenden Kapitel werden die durch Kreuzvalidierung beurteilten Modelle des Random Forest Regressors und der Support Vector Regression untersucht. Das Ziel dieser Evaluation wird sein, die besten Hyperparameter für die jeweiligen Algorithmen zu wählen und für jeden Algorithmus ein adäquates Modell zu trainieren. Diese Modelle werden auf die Testdaten angewandt und sollten damit auch eine gute Generalisierung erreichen.
Im Nachfolgenden werden die Ergebnisse des Hyperparametertrainings für den Random Forest Regressor dargestellt. Man sieht hier deutlich, dass wir den Besten Mean Squared Error auf den Validierungsdaten bei einer Baumtiefe (max_depth) von 23 und einer minimalen Anzahl an Spaltungen (min_sample_split) von 2 erreichen.
Bei den Funktionen zur Berechnung der maximalen Anzahl an Features, die für eine Aufteilung betrachtet werden, stechen zwei Funktionen heraus. Dies wäre zum Einen die Wurzelfunktion (sqrt), welche von Scikit-Learn durch $round(sqrt(11))$ berechnet wird und zum anderen die Funktion des Logarithmus Dualis, welche durch Scikit-Learn mit $round(log2(11))$ dargestellt wird.
Bei 11 Features ergibt sich, dass die beide Funktionen dasselbe Ergebnis liefern:
$round(log2(11)) = round(sqrt(11))$
Dies ist uns leider erst nach dem Durchlauf der Hyperparameter aufgefallen. Im Laufenden werden wir mit der Wurzelfunktion weiterarbeiten.
df = pd.read_csv('results/train_conf_tree.csv')
df=df.sort_values(by=['mse_val'])
df.head(5)
| n_estimators | max_depth | min_samples_split | min_weight_fraction_leaf | ccp_alpha | oob_score | max_features | r2score_train | mse_train | acc_train | r2score_val | mse_val | acc_val | time | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1000 | 23 | 2 | 0 | 0 | True | sqrt | 0.932157 | 0.051272 | 0.958235 | 0.490865 | 0.384372 | 0.649588 | 6.287473 |
| 1 | 1000 | 23 | 2 | 0 | 0 | True | log2 | 0.932157 | 0.051272 | 0.958235 | 0.490865 | 0.384372 | 0.649588 | 6.258244 |
| 2 | 1000 | 22 | 2 | 0 | 0 | True | sqrt | 0.931837 | 0.051515 | 0.957938 | 0.490420 | 0.384711 | 0.651959 | 6.288148 |
| 3 | 1000 | 22 | 2 | 0 | 0 | True | log2 | 0.931837 | 0.051515 | 0.957938 | 0.490420 | 0.384711 | 0.651959 | 6.350337 |
| 4 | 1000 | 29 | 2 | 0 | 0 | True | sqrt | 0.932390 | 0.051096 | 0.957642 | 0.490034 | 0.385001 | 0.648997 | 6.302474 |
Die dreidimensionalen Darstellungen zeigt die Veränderung des Mean Squared Errors mit verändernder maximaler Tiefe (max_depth) und minimaler Aufteilung der Features (min_sample_split).
Zur Ermittlung der optimalen Baumtiefe wird folgend eine zweidimensionale Darstellung verwendet, da hier das Optimum besser erkennbar ist.
plot_rfr3d()
In den beiden unterliegenden Grafiken wird jeweils der Mean Squared Error über die Abhängigkeit der maximale Tiefe und der minimalen Aufteilung der Features dargestellt.
In der ersten Grafik wird dabei die maximale Tiefe der Bäume auf 23 gesetzt und die max_feature Methode sqrt verwendet. Wie bereits oben erläutert, bildet diese Kombination die besten Ergebnisse unser Hyperparametersuche ab. Ab einer Tiefe von 20 wird hier erkennbar, dass sich die Ergebnisse kaum verbessern. Das Optimum liegt hierbei bei einer Baumtiefe von 23. Zudem ist erkennbar, dass sich die Laufzeit bei höherer maximaler Tiefe nicht mehr stark verändert. Dies liegt daran, dass bei einer Tiefe von 23 die maximale Tiefe bereits erreicht ist.
In der zweiten Grafik wird eine minimale Aufteilung der Features von zwei und die max_feature Methode sqrt verwendet. Hier wird deutlich, dass die kleinste Aufteilung von 2 Featuren die besten Ergebnisse Erzielen.
plot_rfr2d_2()
Durch die vorherige Evaluation der verschiedenen Modelle ergibt sich, dass der Random Forest Regressor bei einer maximalen Tiefe größer 20 und einer minimalen Aufteilung der Features von 2 die besten Ergebnisse erzielt. Da es ersichtlich ist, dass das Model mit dem geringesten MSE auf die Validationsdaten hier die beste Wahl darstellt, wird für die maximale Tiefe der Wert 23 festgelegt.
Im Folgenden werden die von uns gewählten Hyperparametern mit ihren erzielten Metriken dargestellt:
# Hyperparameter des ausgewählten Modells
df = pd.read_csv('results/train_conf_tree.csv')
df = df.sort_values(by=['mse_val'])
best_config_tree = df.iloc[0].to_dict()
best_config_tree
{'n_estimators': 1000,
'max_depth': 23,
'min_samples_split': 2,
'min_weight_fraction_leaf': 0,
'ccp_alpha': 0,
'oob_score': True,
'max_features': 'sqrt',
'r2score_train': 0.9321572452223404,
'mse_train': 0.0512718609771633,
'acc_train': 0.95823472695263,
'r2score_val': 0.4908645412701974,
'mse_val': 0.3843721213738536,
'acc_val': 0.6495883165581211,
'time': 6.287473440170288}
Im folgenden Kapitel werden die Ergebnisse der Support Vector Regression ohne Anwendung der Feature Selection evaluiert, um anschließend die Hyperparameter für ein adäquates Modell wählen zu können.
An der Ausgabe der Hyperparameter und deren Validierungs-/Trainingsergebnisse sieht man sehr gut, dass der Durchlauf des Support Verctor Regressors mit der Skalierfunktion StandardScaler die besten Ergebnisse erzielt.
df = pd.read_csv('results/train_conf_svr.csv')
df=df.sort_values(by=['mse_val'])
df.head(5)
| kernel | epsilon | C | gamma | degree | r2score_train | mse_train | acc_train | r2score_val | mse_val | acc_val | scaler | time | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | rbf | 0.25 | 1.429461 | 0.31622776601683794 | 0 | 0.808053 | 0.145069 | 0.898253 | 0.385928 | 0.463565 | 0.605451 | StandardScaler() | 2.750675 |
| 1 | rbf | 0.30 | 1.429461 | 0.31622776601683794 | 0 | 0.791919 | 0.157263 | 0.901659 | 0.385446 | 0.463923 | 0.607228 | StandardScaler() | 2.621991 |
| 2 | rbf | 0.25 | 1.126482 | 0.31622776601683794 | 0 | 0.776587 | 0.168851 | 0.870557 | 0.385359 | 0.464009 | 0.605155 | StandardScaler() | 2.657069 |
| 3 | rbf | 0.20 | 1.126482 | 0.31622776601683794 | 0 | 0.787608 | 0.160522 | 0.865225 | 0.385237 | 0.464100 | 0.599230 | StandardScaler() | 2.794530 |
| 4 | rbf | 0.20 | 1.429461 | 0.31622776601683794 | 0 | 0.820345 | 0.135780 | 0.892772 | 0.384590 | 0.464578 | 0.606636 | StandardScaler() | 2.889254 |
In den beiden unterliegenden Grafiken wird jeweils der Mean Squared Error über die Abhängigkeit der Regularisierungskonstante C und dem Parameter Epsilon dargestellt.
Es ist wie oben erneut erkennbar, dass der StandardScaler bessere Ergebnisse als der MinMaxScaler erreicht. Aus diesem Grund werden hier bereits ausschließlich diese Modelle betrachtet.
In der ersten Grafik ist deutlich zu erkennen, dass die Zeitkomplexität mit größer werdendem Epsilon linear abnimmt.
Die zweite Grafik zeigt, dass der ideale Mean Squared Error bei einer Regularisierungskonstante von etwa 1,429 liegt. Da die Regularisierung im Funktionsaufruf von Scikit-Learn proportional invers zu C ist, bedeutet dies für unser Modell, dass die Toleranz gegenüber größerer Gewichte zu besseren Ergebnissen führt.
plot_svr2d()
In den unteren beiden Grafiken wird der Mean Squared Error abhängig von den beiden Parameter C und Epsilon noch einmal dreidimensional dargestellt.
plot_svr_3d()
Im Folgenden Kapitel werden die Ergebnisse der Support Vector Regression mit Anwendung der Feature Selection evaluiert um anschließend das beste Modell wählen zu können.
In der Ausgabe der Hyperparameter und deren Validierungs-/Trainingsergebnisse sieht man sehr gut, dass der Durchlauf des Support Vector Regressors mit der Scikit-Learn Funktion MinMaxScaler die besten Ergebnisse erzielt. Aus diesem Grund werden hier bereits ausschließlich Modelle betrachtet, bei der die Daten mit Hilfe von MinMax skaliert wurden.
Für den Parameter Gamma wird der von Scikit-Learn vorgegebene Wert "scale" verwendet.
df = pd.read_csv('results/train_conf_svr_feat_sel.csv')
df=df.sort_values(by=['mse_val'])
df.head(5)
| kernel | epsilon | C | gamma | degree | r2score_train | mse_train | acc_train | r2score_val | mse_val | acc_val | scaler | time | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | rbf | 0.25 | 0.699564 | scale | 0 | 0.357370 | 0.485698 | 0.578348 | 0.293147 | 0.533736 | 0.547690 | MinMaxScaler() | 2.292870 |
| 1 | rbf | 0.25 | 0.887720 | scale | 0 | 0.364004 | 0.480685 | 0.582642 | 0.292724 | 0.534056 | 0.546801 | MinMaxScaler() | 2.296838 |
| 2 | rbf | 0.25 | 0.551289 | scale | 0 | 0.351147 | 0.490401 | 0.574349 | 0.292262 | 0.534406 | 0.546506 | MinMaxScaler() | 2.263947 |
| 3 | rbf | 0.20 | 0.699564 | scale | 0 | 0.356163 | 0.486611 | 0.577163 | 0.292192 | 0.534473 | 0.545915 | MinMaxScaler() | 2.355726 |
| 4 | rbf | 0.25 | 1.126482 | scale | 0 | 0.370623 | 0.475683 | 0.587530 | 0.291829 | 0.534728 | 0.547097 | MinMaxScaler() | 2.344709 |
In der dreidimensionalen Grafik wird der Mean Suqared Error in Abhängigkeit von den Parametern C und Epsilon grafisch dargestellt. Bereits hier ist zu erkennen, dass unsere Modelle bei Andwendung von Feature Selection eine schlechtere Vorhersage auf die Validierungsdaten vorweisen.
Die Ursache dafür kann am Informationsverlust liegen, wenn Features durch die Feature Selection nicht in den Lernprozess aufgenommen werden.
plot_svr_feat_sel3d()
plot_svr2d_feat_sel()
Es wird nur ein Modell für die SVR ausgewählt. Da der Support Vector Regressor bessere Ergebnisse auf den nicht selektierten Datensatz erzielt, wird diese Vorgehensweise gewählt. Aus diesem Grund wird nur ein Modell auf den Datensatz ohne Feature Selection trainiert .
# Hyperparameter des ausgewählten Modells
df = pd.read_csv('results/train_conf_svr.csv')
df = df.sort_values(by=['mse_val'])
best_config_svr = df.iloc[0].to_dict()
best_config_svr
{'kernel': 'rbf',
'epsilon': 0.25,
'C': 1.4294613383568446,
'gamma': '0.31622776601683794',
'degree': 0,
'r2score_train': 0.8080529387016915,
'mse_train': 0.1450693197797238,
'acc_train': 0.8982526284614245,
'r2score_val': 0.3859280363707231,
'mse_val': 0.4635654466182942,
'acc_val': 0.605451220314453,
'scaler': 'StandardScaler()',
'time': 2.7506747245788574}
Hier werden die oben ausgewählten Modelle erneut auf den Trainingsdatensatz trainiert, um sie anschließend auf dem Testdatensatz, welcher zu Begin zur Seite gelegt wurde, bewerten zu können.
train_df, test_df = get_datasets(logarithm=True, feature_selection=False)
X_train = train_df.drop("quality",axis=1).values
X_test = test_df.drop("quality",axis=1).values
y_train = train_df["quality"].values
y_test = test_df["quality"].values
rfr_model = RandomForestRegressor_train(X_train, y_train, hyperparameter = best_config_tree, cross_validation = False)
svr_model = SupportVectorRegressor_train(X_train, y_train, cross_validation=False, hyperparameter=best_config_svr, kernel = "rbf")
In der folgenden Grafik werden die Regressionsmetriken der Genauigkeit und Mean Squared Error dargestellt. Da unsere Zielvariable aus diskreten Werten besteht und unsere Regressionsvorhersagen stetig sind, muss zur Berechnung der Genauigkeit der Vorhersagewert gerundet werden.
Der Random Forest Regressor erzielt gute Ergebnisse auf allen Datensätze. Die deutlich besseren Ergebnisse auf den Trainingsdatensatz lassen auf eine hohe Varianz deuten.
Das Modell erzielt nahezu die gleichen Ergebnisse auf Test- und Validierungsdatensatz.
y_pred_rfr = rfr_model.predict(X_test)
plot_metrics(y_test, y_pred_rfr, best_config_tree, modelname = "RFR")
Die folgende Tabelle zeigt die Wichtigkeit der Features auf die Vorhersage. Wie bereits erwartet, hat der Alkoholgehalt bzw der logarithmierte Alkoholgehalt den größten Einfluss auf die Vorhersage des Modells.
Im Kapitel Datenanalyse wurde bereits festgestellt dass das Feature Alkoholgehalt eine mäßig-starke Korrelation zur Zielvariablen Qualität aufweist.
plot_rfrfeatureimportance(rfr_model, train_df)
Hier wird die Vorhersage des Modells noch einmal den wahren Werten gegenübergestellt, dabei werden sowohl die gerundeten Vorhersagen als auch die stetige Vorhersage dargestellt.
plot_histograms(y_test, y_pred_rfr, modelname = "RFR")
Die Confusion Matrix gibt uns etwas mehr Aufschluss über die Qualität unseres Modells. Hier werden zusätzlich für alle Klassen der Recall und Precision berechnet.
Recall: $\frac{TP}{TP+FN}$
Precision $\frac{TP}{TP+FP}$
Man kann der Tabelle entnehmen, dass für die Qualitäten 8 und 4 eine sehr hohe Precision berechnet wurde, was daran liegt dass wenige Datenpunkte dieser Klasse sehr gut vorhergesagt werden konnten. Der hier interessantere Recall Wert gibt uns jedoch Aufschluss darüber, dass viele Weine der Qualität 4 und 8 nicht richtig klassifiziert wurden.
Ein besseres Ergebnis sieht man bei den Weinen der Qualität 5,6 und 7. Dies ist wenig überraschend, da für diese Klassen die meisten Daten zur Verfügung standen.
plot_confusion_matrix(y_test, y_pred_rfr, modelname = "RFR", datensatz = "(Testdatensatz)")
plot_correct_prediction_pairplot(y_test, y_pred_rfr, test_df)
In der folgenden Grafik werden die Regressionsmetriken der Genauigkeit und Mean Squared Error dargestellt.
Wie zuvor der Random Forest Regressor erzielt auch der Support Vector Regressor sehr gute Ergebnisse. Das Modell performt auf die Testdaten ähnlich gut wie auf den Validierungsdaten. Es ist allerdings wieder klar zu erkennen, dass die Genauigkeit, als auch der Mean Squared Error auf den Trainingsdaten deutlich besser ist.
y_pred_svr = svr_model.predict(X_test)
plot_metrics(y_test, y_pred_svr, best_config_svr, modelname="SVR")
Hier wird die Vorhersage des Models noch einmal den wahren Werten gegenübergestellt, dabei werden sowohl die gerundeten Vorhersagen als auch die stetige Vorhersage dargestellt.
plot_histograms(y_test, y_pred_svr, modelname="SVR")
Wie schon die Confusion Matrix bei dem Random Forest Regressor zeigt sich der unausgeglichene Datensatz ebenfalls in den Ergebnissen der Confusion Matrix des Support Vector Regressors.
plot_confusion_matrix(y_test, y_pred_svr, modelname="SVR", datensatz="(Testdatensatz)")
plot_correct_prediction_pairplot(y_test, y_pred_svr, test_df)
Zusätzlich zu den oben beschriebenen Modellen, wurde ein Voting Ensemble der beiden Algorithmen erstellt.
Aus den anschließenden Plots ist zu erkennen, dass das erstellte Ensemble Modell nicht wesentlich verbessert. Dies könnte daran liegen, dass der Random Forest Regressor bereits intern ein Ensemblemodell aus vielen verschiedenen Entscheidungsbäumen ist und bereits bessere Ergebnisse als der Support Vector Regressor erzielt.
y_pred = np.mean(np.asarray([svr_model.predict(X_test), rfr_model.predict(X_test)]),axis = 0)
plot_metrics_ensemble(y_test, y_pred, predictions=[y_pred_svr, y_pred_rfr], modelname="SVR")
plot_histograms(y_test, y_pred, modelname="Ensemble Modell")
plot_confusion_matrix(y_test, y_pred, modelname="Ensemble Modell", datensatz="(Testdatensatz)")
Die Ergebnisse beider Modelle sind vorzeigbar. Beide Modelle haben einen guten Mean Squared Error auf den Testdatensatz. Das Random Forest Regressor Modell hat dabei bessere Ergebnisse als der Support Vector Regressor erzielt. Die Feature Selection hat bei diesem Datensatz zu starkem Informationsverlust und somit zu deutlich schlechtere Ergnissen geführt.
Die schlechteren Ergebnisse bei den weniger vertretenen Klassen waren zu erwarten und akzeptabel, da diese auf Sicht des gesamten Datensatzes nur in sehr kleiner Anzahl vorkommen. Eine Gewichtung oder Oversampling dieser Gruppen zur Verschlechterung der Precision der häufigeren vorkommenen Klassen führen. Dies kann dazu führen, dass Modelle auf zukünftige Daten die Vorhersage der weniger vorkommenen Klassen präferenzieren und somit die Klassenverteilung der Vorhersage und die der realen Werte abweichen.
Grundsätzlich muss man mit diesem Datensatz kritisch umgehen da die subjektive Einordnung durch Weinexperten keine wissenschaftlich basierte Einordnung ist und schlechtere Ergebnisse von Modellen auch auf eine Inkonsistenz dieser Einordnung zurückzuführen werden könnte.